This literature review investigates the morphological and behavioral significance of the horns of Carnotaurus sastrei, a theropod dinosaur from the Late Cretaceous period. Through a comprehensive analysis of fossil specimens, comparative anatomy, and biomechanical modeling, this review explores the evolutionary adaptations and potential functions of these distinctive cranial structures. The horns of Carnotaurus are hypothesized to serve multiple roles, including species recognition, thermoregulation, and intraspecific combat. Our findings suggest that its cranial horns likely served a primary role in species recognition, intimidating rivals and signaling mating readiness. It also could have been used occasionally in head-butting contests, potentially as a display of dominance, but likely did not play a role in thermoregulation. Additionally, we examine the ecological context in which Carnotaurus lived, assessing how environmental factors could have influenced the development of such features. The implications of this study extend to broader discussions on the functional morphology and adaptive strategies of theropod dinosaurs, highlighting the complex relationship between form and function in the evolutionary history of predatory dinosaurs like Carnotaurus sastrei.

The study describes the features of manifestations and interrelationships of job stress, working capacity, professional performance and safety in loggers with shift work organization in the North. The study involved 402 loggers. The research methods include questionnaires and psychophysio-logical diagnostics of stress and working capacity, as well as questionnaires on the professional performance and safety of workers. The following statistical methods were used: correlation, mul-tivariate dispersion and multi-regression stepwise analysis. It was found that the severity of stress, speed, accuracy and operator working capacity, as well as well-being, activity and mood in logging equipment operators, timber truck drivers and maintenance specialists statistically differ signifi-cantly. Higher professional stress and more frequent decrease in professional performance are characteristic of truck drivers. Psychological and psychophysiological job stress and working ca-pacity parameters are associated with professional performance parameters of loggers. According to the results of a number of multi-regression analyses, reduced professional performance markers of loggers include the index of stress, satiety, monotony and fatigue, vegetative balance and stress (method of M. Luscher and coefficients of G.A. Aminev), operator working capacity and reaction speed (CVMR).

Menstruation is a significant periodical factor in women's lives, affecting them from menarche to menopause. This study investigates the menstrual status and its impact on the performance of Korea Ladies Professional Golf Association (KLPGA) 1st Tour players using Latent Profile Analysis (LPA). The study involved 119 female KLPGA tour license professionals who participated in over 30 tournaments annually, requiring them to manage their menstrual cycles during competitions. A questionnaire collected data on demographics, menstrual cycle characteristics, and training hours. Four distinct player profiles were identified based on self-esteem, anxiety, and perceived performance. Profile 4 exhibited the highest self-esteem and perceived performance with the lowest anxiety levels, while Profile 1 showed the highest anxiety levels and lowest self-esteem. Cross-tabulation and ANOVA analyses highlighted significant differences in practice hours and athletic experience across profiles. The findings suggest that regular menstrual cycles and athletic experience are crucial in defining player profiles. These insights are valuable for coaches and professionals to develop tailored training and management strategies to enhance performance. Future research should expand the sample size and employ longitudinal methods to validate these results.

This paper is intended to correlate the impact of leadership skills on organizations' performance, all organizations grow differently, and their growth depends mostly on positive performance from one year to another which has direct correlations to the leadership dreams, visions, foresight and aspirations for the organization. There is one thing for the leader to have vision, but the leader needs to have followership to assist in implementing their vision to make it goals which translate to performance in the organization and growth. The leadership style or management skills greatly influence how they command and motivate followership to actualize their dreams or the organizational visions and mission which results in the organization's performance. A positive leadership influence produces or actualizes a positive organisational performance that will move the organization towards the vision of the organization. Knowing the difference between a manager and a leader is pertinent in explaining the correlation between leadership and organizational performance. The understanding of these two roles provides credence to the correlation between effective leadership and organisational performance, and the understanding of the term, the use and the importance of strategic management to leadership and organizational performance. There is a wide difference between managers and leaders, which is based on personality and their approach to the resolution of challenges they are confronted with.

Timor-Leste, since its independence in 2002, has faced challenges in managing the growing number of civil servants, currently numbering over 13,000. Civil servants are classified under two regimes: General (GCR) and Special (SCR). This classification leads to disparities in salary, benefits, promotions, and performance evaluations, creating dissatisfaction among employees in both regimes. GCR employees enjoy regular salary increases and promotions based on performance, whereas SCR employees, despite earning higher salaries, do not receive the same opportunities for career advancement. This policy paper analyses these differences and recommends abolishing the dual regime structure. It proposes a unified system where salary progression, benefits, and promotions are based on education level, service length, and performance evaluations. Additional allowances should be provided to those working in rural areas to encourage retention and equitable service delivery. Regular external monitoring and audits are essential for effective performance management. Evidence from Indonesia supports these recommendations, showing that additional allowances and strong leadership improve employee performance and discipline.

Background/Objectives: Multiple sclerosis (MS) is a chronic neurological disorder characterized by various clinical presentations and manifestations that include biopsychosocial impediments. This study has three interrelated goals relevant to biopsychosocial functioning. The first is to compare cognitive, neuropsychological, and affective functioning and quality of life between patients with MS (PwMS) and a control group. The second is to examine whether cognitive and neuropsychological performance is affected by gender, and the third is to examine whether variation in QoL hinges on cognitive neuropsychological performance. Methods: This multicenter study was carried out among clinically stable PwMS under follow-up in two tertiary care units in urban Oman. Healthy controls, matched for age and sex, were also recruited as a comparison group. Data were collected using cognitive batteries sensitive to current reasoning ability and conventional neuropsychological batteries designed to measure verbal learning, visual-spatial ability, and processing speed. The affective range (anxiety and depressive symptoms) and quality of life (QoL) were also assessed. Results: The PwMS group scored lower on current reasoning ability, verbal learning, visual-spatial ability, and processing speed compared with the control group. The incidence of anxiety was higher in the PwMS group but there was no statistically significant difference in depressive symptoms. No significant differences were found in cognitive variables between the two sexes, except in visual-spatial ability, where women outperformed men. PwMS with low QoL scored lower on the attention and concentration indices than those with adequate QoL. According to QoL, no significant differences were observed in reasoning, verbal learning, and visual-spatial ability. Conclusions: The present sentinel study suggests that the Omani cohort with MS tends to have lower indices of current reasoning ability, visual and spatial memory and cognitive speed compared to control subjects. Gender differences are minimal, except for visual-spatial abilities where women outperform men. Quality of life significantly affects cognitive functioning. In general, the biopsychosocial impediment appears to be significant, indicating the need for comprehensive evaluation and care in the management of MS.

At present, under the background of high-quality development and the “carbon peaking and carbon neutrality” goal, China’s economic structure, industrial structure and energy structure have all begun green transformation and upgrading. The supply chain has become an important starting point for energy conservation and carbon reduction. In this context, enterprises have also ushered in huge environmental risk challenges and innovative development opportunities. This paper adopts Entropy-Weighted TOPSIS comprehensive evaluation method to analyze the green supply chain performance of "B" company, a new energy leading company, based on the theory of green development and corporate social responsibility. By establishing a green supply chain evaluation criteria system including four dimensions of finance performance, environment performance, operation performance and innovation performance, the weight of each evaluation criterion is objectively analyzed and calculated, and the green supply chain performance of "B" company from 2018 to 2022 is ranked. Based on this, comprehensive evaluations and sub-dimension evaluation are carried out and suggestions for improvement are put forward. At the same time, we hope to help other new energy vehicle companies optimize their own green supply chain practice mode.

The past 40 years have seen automotive Electronic Control Units (ECUs) move from being purely mechanical controlled to being primarily digital controlled. While there has been significant improvements in terms of passenger safety and vehicle efficiency including optimised fuel consumption, rising ECU numbers have resulted in increased vehicle weight, greater demands placed on power,more complex hardware and software, ad-hoc methods for updating software, and subsequent rise in costs for both vehicle manufacturer and consumer. To address these issues, the research presented in this paper proposes virtualisation technologies to be applied within automotive Electrical/Electronic (E/E) architecture. To proposed approach is evaluated through a comprehensive study of the CPU and memory resource requirement in order to support container-based ECU automotive functions. This comprehensive performance evaluation reveals that lightweight container virtualisation has the potential to welcome a paradigm shift in the E/E architecture, promoting consolidation and enhancing the architecture through power, weight and cost savings. Container based virtualisation will also enable a robust mechanism to facilitate online dynamic software updates throughout the lifetime of a vehicle.

The Sustainable Development Center of the University of Brasilia is one of the modernist buildings that make up the Darcy Ribeiro campus. The architectural project contains several recommendations for the execution of the flat roof waterproofing system, as well as details for rainwater runoff and drainage, which reveals a certain concern with watertightness. The research seeks to identify the relationship between the pathological manifestations recognized on the roof and the semicircular shape of the building, assessing the state of conservation through the use of damage maps as an analysis tool. The article is based on a field survey using aerophotogrammetry with a drone, the application of vector drawing software for graphic representation and discussion of the possible causes, agents and mechanisms of degradation at work. The results show the importance of mechanical protection for the good performance of the waterproofing system, as well as the need for correct sizing of expansion joints in order to absorb and relieve the stresses caused by hygrothermal variations. The methodology incorporated proved to be effective and economical in diagnosing and monitoring pathological manifestations, making it possible to plan maintenance actions that extend the useful life and preserve the intrinsic characteristics of building systems.

Background: There has been a lack of tools to identify listening difficulties in school settings for both hearing and hearing-impaired Italian students. Thus, the present study aimed to realize cross-cultural adaptation and validation of the Listening Inventory for Education-Revised for Italian students (LIFE-R-ITA). Methods: Following the validation of two forward-backward translations by a multidisciplinary committee, the content validation for the LIFE-R-ITA was performed by pre-testing six implanted children (8-18 years old). After minor cross-cultural adaptations, normative data were collected from a sample of 223 hearing students enrolled in different school settings and educational degrees. Results: For the LIFE-R-ITA, hearing students showed an average score of 72.26% (SD=11.93), reflecting some listening difficulties. The subscales (LIFE total, LIFE class, and LIFE social) indicated good internal consistency. All items were shown to be relevant. Most challenging situations happened when listening in large rooms, especially when other students made noise. LIFE social scores were significantly worse than those of LIFE class (p < 0.001). Conclusions: The LIFE-R-ITA may support teachers and clinicians in assessing students’ self-perception of listening at school. Such understanding may help students overcome their listening difficulties, by planning and selecting the most effective strategies among classroom interventions.

This study investigated the aerodynamic performances of various trains with different nose shapes, using as design variables two angles α,β for the heads shape and the bluntness angle γ, without crosswind. The effect on aerodynamic performances, such as the train drag coefficient, pressure distribution along the train surface, flow structures around the train and the wake, head pressure pulse, were analyzed. The results indicate that the increase of the train nose length for flat shapes decreases the CD values by 21.47% and 19.11%, decreasing the high-pressure region in the leading head. The duck-nose configuration emerges as a compromise between drag reduction and nose length. Increasing the angle γ a further drag reduction of 8.5% is featured. Drag formation along the train is also analyzed. The steeper the variation of the geometry, the higher the peak intensity and the slope of the curve. Regarding the flow features around the train, two-main counter-rotating vortices are captured in the wake. Moreover, the higher the nose length and the higher the bluntness angle γ, the weaker and narrower the wake. Again, a longer nose shape yields to a softer jump in terms of pressure difference, crucial for train homologation and safety.

This Research is to analyze the effect of Intellectual Quotient (IQ), Emotional Quotient (EQ), and Spiritual Quotient (SQ) to the employee performance of Inspectorate South Kalimantan Province. All of The employee are involved as the samples, 81. Data are the perception of the employee regarding the variables. Technique of analysis is using multiple linear regression. Tests involved are Model Test (F), t Test, and classic Assumption test. Significant Test is connected to pvalue. The results show that (1) Intellectual Quotient (IQ) is influencing insignificantly to the employee performance; (2) Emotional Quotient (EQ) is influencing insignificantly to the employee performance; (3) Spiritual Quotie nt (SQ) is influencing significantly to the employee performance. The results also indicate that such effects need further research. Variables should be considered are attitude, operating standar and Technology.

To enhance the uplift capacity and facilitate the installation of multi-row perfobond connectors at shallow burial depths, this study puts forward a novel notched T-perfobond connector. The design incorporates an integrated flange at the bottom of the connector and a notch at the edge of the hole. Through pull-out model tests on four notched T-perfobond connectors, this research investigates their failure mechanisms and pull-out capacities. Utilizing the explicit dynamics method in Abaqus, a finite element model of the pull-out resistance test for the notched T-perfobond connector is established and verified against experimental data. Furthermore, a detailed parametric analysis involving 54 models is conducted, examining crucial parameters such as rib dimensions, hole geometry, flange size, notch width, bar diameter, and material properties. Based on the combined experimental and numerical results, the paper assesses the suitability of current formulas for calculating the pull-out capacity of perfobond connectors and proposes a refined calculation method specifically for notched T-perfobond connectors. All the findings in this paper can serve as a reference in the design and construction of composite structures.

This study investigated the development of novel probiotic formulations specifically designed for rainbow trout aquaculture. The project evaluated the effects of two formulations containing potential probiotic strains isolated from rainbow trout itself. These effects were assessed on various parameters including growth performance, immune response, liver enzyme activity, gene expression related to immunity, and the composition of the bacterial gut microbiota in rainbow trout (Oncorhynchus mykiss). In a completely randomized experimental design, a total of 450 rainbow trout were randomly divided into 70-liter fiberglass tank. The study included six treatments of three replicates (n=18 tanks). Six dietary treatments were included (A) and (B) containing three strains of Pediococcus sp P15, Lactococcus lactis ml3, Weissella cibaria ml6 at two dosages (300 and 500 mg/kg), treatments (C) and (D) containing five strains of P. sp P15, L. lactis ml3, W. cibaria ml6, Enterococcus faecium E10 and Lactobacillus curvatus 13A at two dosages (300 and 500 mg/kg), a commercial probiotic (E) at 300 mg/kg, and a control group (F) without probiotics. Treatments of (A), (B) and (E) resulted in the highest final weights in compared to control group. Fish fed treatments (A) and (B) had the lowest FCR than other groups. Treatments (A) and (D) showed a significant increase in immunoglobulin M (IgM) concentration compared to other groups. The expression of tumor necrosis factor (TNF) was significantly lower in group (A) than the control. In contrast, the expression of interleukin 6 (IL6) and immunoglobulin T (IgT) was increased 4.4-fold and 41-fold, respectively, in group (A) compared to control group. Among the probiotic fed treatments, group (A) showed a significant higher number of lactic acid bacteria compared to other groups during the experiment. This study highlights the significant role of treatment (A) containing three strains of P. sp P15, L. lactis ml3, and W. cibaria ml6 at a dosage of 300 mg/kg as a potential probiotic product for the rainbow trout industry.

This study aimed to evaluate the effects of plasma treated metal contaminated water, used for irrigation, on plant growth. Zinc (Zn) is one of the more commonly used metals. It can enter the environment from industrial processes as particles released into the atmosphere or as wastewater discharged into waterways or the ground. Exposure to large amounts of zinc, even for a short time, can seriously affect human health. In this experiment, three different DBD O2 plasma treated zinc contaminated water and a control (tap water) were used, with Arabidopsis thaliana as the model plant. The treatments were: i) Control, ii) Zn water, iii) Zn+O3(30 min), and iv) Zn+O3(60 min). Arabidopsis plant exhibited maximum growth in the Zn+O3(30 min) treatment. All growth parameters, except leaf area, followed this trend: Zn+O3(30 min) > Control > Zn water > Zn+O3(60 min). Gene expression analysis revealed that reduced metal ion stress and controlled oxidation due to active oxygen species contributed to favorable/improved growth of Arabidopsis in the Zn+O3(30 min) treatment. Therefore, 30 minutes of DBD O2 plasma treated zinc contaminated water [Zn+O3(30 min)] can mitigate the adverse effects of excess zinc ions and promote the growth of Arabidopsis plants.

This qualitative study explores the challenges and successes in supplier development from the perspectives of procurement managers across diverse industries. Through in-depth interviews, key themes emerged, highlighting the critical role of communication, trust, performance measurement, capacity building, risk management, innovation, regulatory compliance, and technology integration in supplier relationship management. Procurement managers emphasized the importance of clear, continuous communication and trust-building activities to align objectives and foster collaborative partnerships. Performance measurement was crucial for evaluating and improving supplier performance, supported by capacity-building initiatives to enhance supplier capabilities. Risk management strategies focused on identifying and mitigating risks, while compliance efforts aimed to ensure adherence to industry standards. Innovation and technological integration were pivotal for driving efficiency and competitiveness, enabling faster time-to-market and improved product quality. Cultural sensitivity and relationship strengthening emerged as essential for navigating diverse cultural contexts and enhancing partnership effectiveness. Overall, the findings underscored positive outcomes including enhanced quality, cost efficiencies, and increased resilience within supply chains. This research contributes valuable insights into effective supplier management practices, emphasizing the strategic importance of supplier development initiatives for sustainable growth and competitive advantage in today's dynamic business environment.

Pharmaceutical packaging is very crucial in as much as it plays the role of enhancing the stability, efficacy as well as safety of the produced medicine through the material used in packaging. It is important to note that cGMP Chapters 661 and 671 are focused on explaining how one should assess the quality of container materials in the sphere of pharmaceuticals. These chapters encompass a number ofmatters among them being Plastic and glass containers and performance testing; they serve as a resource that aids in assuring all standards are met with profound proficiency. Following this, the performance of two core chapters of USP known as Chapter 661 on “Containers—Glass” and Chapter 671 on “Containers—Performance Testing” will be dealt with in a step-by-step manner in the following paper while providing a comprehensive review of both at the same time. Understanding and legal obedience to these rules, as stipulated in the above-mentioned chapter, are indispensable for almost all the parties involved in the production of the drugs, together with the policies and legislation on the same. Thus, the purpose of this paper is to describe and discuss the major aspects of the understanding, application, requirements and evaluation procedures depending on the USP Chapters 661 and 671 in the sphere of the pharmaceutical market.

This paper delves into the comprehensive analysis and investigation of thermodynamic enhancement and exergy optimization of turbofan engines through the integration of fuzzy logic and newest meta-heuristic optimizers, like the Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). In contemporary engineering practices, exergy analysis stands out as a crucial and indispensable tool utilized by numerous engineers and researchers in the design, operation, and performance evaluation of energy systems. Its multifaceted advantages include the precise determination of location, types, and quantification of exergy losses and production. By augmenting exergy efficiency while concurrently curbing exergy destruction, substantial enhancements in engine performance and cost reduction can be achieved. The study focuses on the CF6-80A and CFM56 turbofan engines, scrutinizing individual components such as the fan, low-pressure compressor, high-pressure compressor, combustion chamber, high-pressure turbine, and low-pressure turbine. Key parameters for engine evaluation encompass exergy efficiency, recovery potential, relative exergy destruction, fuel depletion rate, and inefficiency. To conduct a rigorous exergy analysis, engine modeling is imperative, particularly during the cruise phase, which predominantly characterizes engine operation. Subsequently, exergy analysis is executed in accordance with established thermodynamic principles, leveraging equations governing mass conservation, energy conservation, and exergy conservation for each engine component. Further optimization of exergy destruction is achieved through the application of meta-heuristic optimizers and fuzzy logic, facilitating informed decision-making processes.

Nitrogen oxides (NOx), pivotal atmospheric pollutants, significantly imperil the environment and human health. The CH4-SCR process, leveraging the abundant and accessible methane (CH4), emerges as a promising avenue for NOx abatement. Previous studies have demonstrated that zeolite support with twelve-membered ring (12-MR) and five-membered ring (5-MR) structures are susceptible to framework collapse in the presence of water, leading to catalyst deactivation. Consequently, there is a necessity to explore novel zeolites with enhanced hydrothermal stability for application in CH4-SCR processes. This research introduced for the first time an investigation into a novel In-H-SSZ-39 catalyst, synthesized via ion exchange and meticulously optimized for preparation conditions, including calcination temperature, In ions concentraiton, and reaction conditions, including CH4/NO ratio, O2 concentration, water vapor content, and Gas hourly space velocity (GHSV). Notably, the In/H-SSZ-39 catalyst achieved superior performance of 42.1% at 605 °C, with a calcination temperature of 500 °C and an In ion concentration of 0.066 M, under CH4/NO ratio of 1.5:1, 10% O2, and GHSV of 21000 h-1. In addition, the catalytic performance was influenced by the concentration of water vapor and the GHSV value.

This research aims to analyze the impact of Social Responsibility on the performance of 216 European companies during the years 2017 to 2021. The objective of this research is to determine how the operational, financial and market performance of companies is influenced by social responsibility practices. The methodology adopted is quantitative in nature, using the estimation of dynamic models for panel data. To quantify corporate performance, this study will use, the return on assets, the return on equity and finally the Tobin's Q ratio. On the other hand, ESG (Environment, Social and Government) scores and GC Score scores will be used in order to quantify SR. The results show that SR presents not only a negative influence on the financial and operational performance of companies, but also a positive impact on market performance. This influence is even greater when distinguishing the best from the worst scores. The environment, social and government dimension shows a negative relationship with ROA and ROE, and a positive one with Tobin's Q. On the other hand, the anti-corruption and environment dimension of the GC Score, relates negatively with Tobin's Q, the human rights dimension relates negatively with ROE and ROA, and finally, the labor law dimension presents a positive relationship with ROE. Importantly, firm size positively influences this relationship, while age has a negative influence. This research offers important contributions to the literature, since from the ESG scores and the GC Score, a complete analysis of the impact of social responsibility on corporate performance is developed.

This study examines if enterprises’ digital transformation enhances their sustainable development capabilities and reduces carbon emissions, thus enhancing carbon neutrality performance and implementing the "dual-carbon" strategy. It specifically explores the impact of Chinese firms’ digital transformation on carbon neutrality performance in 30 provinces and municipalities in China from 2011 to 2021. Based on the Difference-in-Difference method and spatial econometric modeling, this study finds a U-shaped relationship between enterprise digital transformation and carbon performance, with spatial spillover effects. It also finds that converting environmental charges into taxes can significantly improve carbon performance. In terms of the mechanism of action, digital transformation affects carbon performance by influencing energy use efficiency and adjusting the level of industrial structure advancement and rationalization. In terms of heterogeneity, this U-shaped relationship exists only in the eastern and central regions, and the significance is more substantial in the east; in addition, the impact of enterprise digital transformation on carbon performance is more evident in regions with higher R&D intensity and higher economic development levels. These findings imply that the government should further encourage and guide enterprise digital transformation, monitor the effects of environmental protection policies and select and implement carbon emission reduction strategies according to local conditions to improve carbon performance.

This research aims to investigate psychological anxiety factors, particularly Music Performance Anxiety (MPA), that influence the sustainability of music learning systems. This study employs an innovative integration of qualitative and quantitative methodologies, marking the first use of a nonlinear system paired with a comprehensive data framework for analyzing questionnaire responses. This approach allows for a detailed examination of the effects of these factors on academic outcomes. Previous research has primarily focused on the fragmented music learning system from the perspective of teachers' instructional strategies, emphasizing phased teaching methods and learning objectives which focus often neglected a significant subset of music learners. Addressing this oversight, the current study specifically centers on the emotional aspects of anxiety within music learning systems, with a particular emphasis on students, who play a crucial role in music education. This perspective enables a deep exploration of how MPA and other related emotional factors affect music learning systems. A notable innovation of this research is the development of a stochastic nonlinear system designed to model the psychological factors impacting student music learning, complemented by a quantitative model that assesses actual learning outcomes. By analyzing this nonlinear system, the research identifies weight values for various negative emotions, particularly those related to MPA, that significantly influence the music learning process. The integration of MPA and other anxiety related emotional factors with practical learning outcomes provides a comprehensive understanding of their combined impact on the music learning system. These insights are invaluable for educators and policymakers aiming to enhance both the effectiveness and emotional well-being within music education. This comprehensive approach offers a novel perspective in understanding and improving the dynamics of music education through a more empathetic and scientifically grounded lens.

In this research, the primary goal was to investigate the relationship between strategic planning and organizational performance in Iraq's manufacturing context. The study's primary data sources were 360 manager respondents. The structured questionnaire was used to collect primary data from manufacturing firms located throughout Iraq. To analyze the result, the researcher used descriptive statistics, correlation, and multiple regression analysis. SPSS version 16 software was used to conduct data analysis. The result reveals that the process of strategic planning has a beneficial effect on financial performance. Environmental scanning has a statistically significant positive effect on a company's non-financial performance. Management participation and planning formality positively and statistically significantly affect a business's non-financial performance at the 10 percent level. The domain of strategy and technique has not impacted the company's non-financial performance.

Timber-concrete composite (TCC) systems join the positive aspects of engineered wood products (good seismic behaviour, low thermal conductivity, environmental sustainability, good behaviour under fire if appropriately designed) with those of concrete (high thermal inertia, durability, excellent fire resistance). TCC facades are typically composed by an internal insulated timber-frame wall and an external concrete slab, separated by a ventilated air cavity. However, there is very limited knowledge concerning the performance of TCC facades, especially for what concerns their thermal behaviour. The present paper deals with the development and optimisation of a 2D CFD model for the analysis of TCC ventilated façades thermal behaviour. The model is calibrated and validated against the experimental data collected during the annual monitoring of a real TCC ventilated envelope in the north of Italy. Also, a new solver algorithm is developed to significantly speed up the simulation. The final model can be used for the time-efficient analysis and optimisation of the thermal performance of TCC ventilated facades, as well as other ventilated facades with external massive cladding, avoiding the expensive and time-consuming construction of mock-ups, or the use of comparably slow (conventional) CFD solvers that are less suitable for optimization studies.

The work aims to improve the battery performance in hybrid electric vehicles (HEVs) by reducing the vehicle speed. We develop a specific protocol for managing battery use and optimizing the energy consumption rate to achieve this goal. The protocol automatically controls the driving operation, avoiding incompatible driving patterns with energy-saving mode and performance improvement. The protocol is submitted to a simulation process to predict the energy rate lowering and battery performance enhancement. The proposed protocol applies to any hybrid electric vehicle type and route conditions since it uses vehicle mass, drag and rolling coefficients, and road slope as variable parameters to determine the minimum energy consumption rate. We run experimental tests to validate the simulation data and the proposed protocol. Furthermore, the protocol applies to variable starting vehicle speeds, from 10 to 50 km/h, corresponding to the current driving patterns, sport, normal, and eco, set up by car manufacturers. A reduction of 10% in vehicle speed in urban and peripheral routes achieves a minimum energy rate, enhancing battery management. Current vehicle speed shows a deviation from optimum management of 18% while applying the vehicle speed reduction limits the deviation to 0.2%. Experimental results show a good agreement with simulation data with 94% accuracy. We tested the protocol for urban and peripheral routes with maximum vehicle speed limits of 60 and 90 km/h.

The objective of this study was to investigate the relationship between high-performance work systems and a company’s social performance, taking into account the organizational climate as a situational variable. Specifically, this study aimed to analyze the impact of perceptions of a high-performance work system on the perception of a company’s social responsibility (CSR) among employees of Jordanian companies with an organizational size of 300 or more. This study used 175 valid questionnaires, and SPSS and AMOS 24 were used to test the hypotheses. The results showed that there was a positive relationship between the perception of a high-performance work system and the perception of a company’s CSR. Furthermore, this study found that a positive diversity climate could enhance the positive relationship between the two. These findings suggest that high-performance work systems can contribute to the development of sustainable human resource management systems and that a positive diversity climate is essential in shaping these systems. Based on these results, it is recommended that companies implement HPWSs and encourage workforce diversity to maximize the value of CSR activities and ensure their sustainability.

Sustainable Humanitarian logistics is gaining attention due to increased disasters. It involves various operations to support people's survival efforts. Key characteristics include unpredictable demand, sudden large demand volumes, high stakes in delivery timeliness, and limited resources. However, the complexity and unpredictability of disaster scenarios necessitate robust and adaptable performance measurement models to evaluate the effectiveness of sustainable humanitarian relief logistics (SHRL). This study proposes a novel performance measurement model for sustainable humanitarian logistics and supply chains that integrates the Fuzzy Delphi Method (FDM) and Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) method. In this research, using 115 articles focused on sustainable humanitarian logistics and supply chains, crisis management, and humanitarian aid, this research identified 25 key performance indicators (KPIs) in the initial phase. Following the implementation of FDM, 19 KPIs were identified as crucial for further analysis. These KPIs were then divided into four distinct categories: "Quality," "Accountability," "Operational Excellence," and "Sustainability". Initially, FDM is utilized to reach a consensus among experts concerning KPIs for humanitarian logistics and supply chains. By incorporating the inherent uncertainty and vagueness in expert judgments, FDM refines the list of key performance indicators that reflect the real-life conditions and constraints in disaster operations. Finally, the fuzzy DEMATEL approach was used to analyze interrelationships among factors, identifying cause-and-effect behavior and ranking them, forming a robust theoretical framework. The study concludes with the development of a comprehensive performance measurement model that facilitates the strategic planning and operational assessment of humanitarian organization operations. The integration of FDM and fuzzy DEMATEL methods offers multiple perspectives for decision-making and helps stakeholders identify critical areas for improvement. Based on the acquired results, the KPIs attached to the Quality (P1) aspect of the proposed framework have gained significant importance and main cause in the cause-and-effect relationship which impacts and is helpful to improve the performance of humanitarian organizations in all phases of disaster management. The KPIs prompt delivery (D1), and delivery accuracy (D2) are more significant, while capacity building and training (D19) and delivery compliance (D15) are least significant in SHRL scenarios. This research is expected to support humanitarian organizations in enhancing their capabilities, thereby improving the effectiveness and efficiency of aid delivery in disaster-stricken areas.

In Yaoundé, Cameroon, excessive and inappropriate speeding remains a major public health concern. Part of the problem are the unsafe speed limits, lack of evidence, and effective evaluation of speeding safety performance indicators (SSPIs), and the absence of speed management, hindering the city's ability to mitigate the risks associated with speeding. This study aimed to address this knowledge gap by assessing SSPIs using a well-defined methodology and suggesting speed management strategies. Data on speed, traffic volumes and road attributes were collected from a random selection of 16 representative road sections in Yaoundé. Seven SSPIs were calculated, and weights were assigned to evaluate city-level SSPIs. The findings showed that 66.8% of drivers drive within the speed limit, generally operating at speeds of 54 km/h with a speed variation of 26 km/h. Based on the speed analysis, evidence-based strategies are proposed, and implementing these strategies could potentially reduce fatalities and serious injuries by 16% to 84% across study locations, as indicated by Elvik's model. These findings have significant policy implications for reducing speeding in Yaoundé, and the methodological approach can be replicated in other urban settings. Future research should extend SSPI evaluation to the national level and test the effectiveness of the recommended strategies.

Educational institutions must identify students who are academically struggling to provide them with necessary support to improve their performance. In this context, recommendation systems powered by deep learning techniques are vital for detecting and categorizing such students. These systems help students plan their future by uncovering patterns in their historical academic data. This study introduces a new deep learning model designed to classify academically underperforming students in educational settings. The model incorporates a Gated Recurrent Neural Network (GRU) and includes specific neural network features like a dense layer, max-pooling layer, and the ADAM optimization algorithm. The model's training and evaluation were conducted using a dataset comprising 15,165 student assessment records from various academic institutions. The performance of the developed GRU model was benchmarked against other educational recommendation systems, including Recurrent Neural Network models, AdaBoost, and the Artificial Immune Recognition System v2. The proposed GRU model demonstrated remarkable accuracy, achieving an overall rate of 99.70%.

Yellow nanorod Mg-MOF-74 was obtained by solvothermal synthesis method. XRD、N2 adsorption-desorption isotherms、SEM and TGA results suggest that the particle size of Mg-MOF-74 reaches 400 nm after the introduction of sodium acetate in the precursor of Mg-MOF-74. Besides, the morphology of Mg-MOF-74 was changed from cauliflower to rod particles. At the same time, the BET specific surface area and pore volume of Mg-MOF-74 were also increased a lot. Then the CO2 dynamic adsorption capacity of Mg-MOF-74 was measured by self-made fix bed under 30 ℃、0.1 bar CO2 partial pressure. The results show that the CO2 adsorption capacity of Mg-MOF-74-N2 reaches 3.67 mmol/g and its CO2 adsorption capacity remains unchanged after 10 times CO2 adsorption-desorption cycles.

Over recent years, the swine industry has witnessed the withdrawal of antibiotics and continuous regulation of zinc and copper oxides in the early-life nutrition of piglets. Due to this development, alternative ingredients or additives from plant sources have been tremendously explored. Therefore, this study's objective was to evaluate the effect of dietary supplementation with tannins on weaned piglets’ growth performance, serum antioxidant capacity, and immune status using a meta-analysis approach. With only the inclusion of non-challenged weaned piglets, a total of 16 studies with parameters of interest were deemed eligible after a two-step screening process following a comprehensive literature search in the scientific databases of Web of Science, Scopus, ScienceDirect, PubMed, and Google Scholar. Two main categories of data, including the study’s characteristics and response variables (growth performance, serum antioxidant, and immune indices), were extracted. Applying the random-effects models, Hedges’ g effect size of supplementation with tannins was calculated using the R software to determine the standardized mean difference (SMD) at a 95% confidence interval. Sub-group analysis and meta-regression further explored heterogeneity (PSMD 0.05, I2 50%, n ≥10). Supplementation with tannin reduced average daily gain (p = 0.20) and feed conversion ratio (p 0.01); however, it increased average daily feed intake (p = 0.07) and final body weight (p 0.01). Meta-regression models indicated that tannin dosage and supplementation duration were directly associated with tannins' effectiveness on productive performance. In the serum, the concentration of glutathione peroxidase, superoxide dismutase, and total antioxidant capacity were elevated (p 0.01) in response to tannins supplementation, while malondialdehydes was reduced (p 0.01). Likewise, decreased immunoglobin A (p = 0.47) and increased immunoglobin M and G levels (p 0.01) were detected. In conclusion, dietary supplementation with tannins, particularly with chestnut and grape seed proanthocyanidins, increases the productivity of weaned piglets. At the same time, it is a possible nutritional strategy to mitigate oxidative stress and stimulate gut health. Thus, supplementing chestnut and grape seed proanthocyanidin tannins in the early phase of swine production could be used to alleviate the incidence of diarrhea.

In Active Flow Control (AFC) applications, to activate the boundary layer the use of pulsating flow has notorious energy advantages versus constant blowing/suction jet injections. For a given AFC application, five parameters, jet location and width, inclination angle, frequency of injection and momentum coefficient need to be tuned. Two main devices are nowadays capable of injecting pulsating flow with the sufficient momentum coefficient to delay the boundary layer separation, these are the Zero Net Mass Flow actuators (ZNMFA) and the Fluidic Oscillators (FO). In the present research, a novel FO configuration is analyzed for the first time at relatively high Reynolds numbers, fluid is considered as incompressible. After obtaining the typical linear correlation between the incoming Reynolds number and the outlet flow oscillating frequency, the effect of outlet width and mixing chamber wedge inclination angle dimensional modifications is addressed, modifications of the outlet width are observed to create large variations on the FO performance. The origin of the self-sustained oscillations is also analyzed in the present manuscript and greatly helps in clarifying the forces acting on the jet inside the mixing chamber. In fact we can conclude saying that the current FO configuration is pressure driven although the mass flow forces appear to be a much more relevant than in previous FO configurations studied.

This research investigates the microstructure and mechanical behaviour of a polylactic acid (PLA)-iron (PLI) composite designed to enable magnetic actuation. Tensile specimens of PLI are produced through Fused Filament Fabrication, incorporating diverse printing angles ranging from 0° to 90°, thereby facilitating the creation of a variety of layups. The microstructure of these 3D-printed composites is analysed using X-ray micro-tomography. Furthermore, the tensile mechanical properties of all composites are evaluated, and the findings are deliberated in relation to the conditions of the printing angle. Additionally, the fractography of broken specimens is examined using Scanning Electron Microscopy. The findings indicate that the printing angle plays a significant role in influencing the tensile properties of the 3D-printed PLI composites, particularly in adjusting mechanical anisotropy. Moreover, an optimal layup of 45°/45° is attained, resulting in an enhanced ranking of the tensile performance. These findings related to 3D-printed PLI composites present a cost-efficient option for manufacturing bio-sourced light-adaptive composites through 3D printing, enabling the generation of intricate magnetic actuation performance.

To accurately identify high-quality functional wood with superior mechanical properties and enhance its durability, it is imperative to understand the relationships between the physical and mechanical attributes of diverse wood types. Presently, there exist issues related to accuracy, efficiency, and differentiation in studying these performance correlations. The Liang Kleeman (L-K) information flow theory, a causative analytical approach rooted in fundamental physics principles, offers swift computational capabilities. Furthermore, the coefficient of variation in L-K information flow quantitatively gauges the intensity of causal effects. Therefore, this article adopts a causal artificial intelligence perspective and introduces a wood performance analysis method based on L-K information flow.This study focuses on four Chinese fir varieties, including fast-growing Chinese fir (YKS), red heart Chinese fir (CSH, XXH), and iron heart Chinese fir (XXT). By computing and comparing variation coefficients of L-K information flow for various physical properties and their impact on mechanical properties, causal relationships between these properties are elucidated. These findings are then applied to predict wood mechanical properties, achieving a remarkable maximum accuracy of 90%.In the future, these findings will prove invaluable for the selection of high-quality wood and for improving the manufacturing process to prolong the service life of functionalized wood.

At present, failure definition and damage characteristic curve (DCC) analysis included in the framework to assess bitumen fatigue cracking performance have an inconsistency in ranking bitumen fatigue behaviour. This study utilized two types of self-healing polymers (STP and IPA1w) to modify the neat asphalt (NA), and research four different types of bitumens: NA, STP-modified bitumen, IPA1w-modified bitumen, and styrene-butadiene-styrene modified bitumen (SBSB), to evaluate the above-mentioned framework. All bitumens were subjected to short-term and long-term aging and tested utilizing the Linear amplitude sweep (LAS) test and simplified viscoelastic-continuum-damage (S-VECD) model. The results showed that the SBSB exhibited the highest numbers of loading cycles (in long-term aging analysis) to reach failure points at 25°C, 28°C, and 31°C which were 2290, 2340, and 2510, respectively. However, this bitumen failed to exhibit the best performance in terms of DCC assessment under the same conditions, confirming the above-mentioned inconsistency. Besides, the current failure criterion could not accurately predict bitumen fatigue behaviour under certain test conditions because two R2 values were below 0.1. As a result, this study proposed a new failure definition and failure criterion to overcome these issues. The proposed failure definition agreed with the DCC analysis to rank bitumen fatigue performance, and the proposed failure criterion showed R2 values higher than 0.9. The new framework presented the modified bitumen containing 0.5% of STP as the asphalt binder with the best fatigue cracking performance, according to the selected test conditions.

This article conceptualises the link between firms’ value chains and distribution networks and the requirements for double materiality assessments in contemporary reporting regulations worldwide. The new European Sustainability Reporting Standards (ESRS) and the standards for sustainability reporting issued by the International Sustainability Standards Board (ISSB), called IFRS S1 and IFRS S2, require companies to report their own direct (scope 1) and indirect (scope 2) greenhouse gas (GHG) emissions as well as GHG emissions in their value chains and distribution networks (both scope 3). However, GHG emissions comprise just one dimension of information that is relevant to understand when assessing, managing and reporting the footprints and impacts of a firm and are, therefore, only a fraction of the key performance indicators (KPIs) related to ESG that should be disclosed. Through a case study, this article demonstrates the connection between the due diligence analysis of firms’ value chains and distribution networks, the analysis of the competitive parameters of the business model, the identified impacts, risks and opportunities, and the double materiality perspective. The double materiality perspective prioritises actions based on probability and significance, creating a natural space to identify KPIs. The article concludes by applying the REGS model and illustrating how it can assist firms in identifying relevant KPIs based on double-materiality assessments.

The purpose of the article is to measure, using the VAIC and MVAIC models, the impact of intellectual capital and its elements on the financial performance of Omani industrial companies listed on the Muscat Stock Exchange (MSE) from 2017 to 2021. Regression analysis using the Gretl software was applied to the study of panel data on the activities of 34 industrial companies in Oman, obtained from the official MSE website and from published financial statements. The analysis of literature sources was carried out using bibliometric analysis, the results of which were visualized using the VOSviewer software. To analyze the relationships between financial performance and its determinants (intellectual capital variables and control variables), four types of PERF models were developed, based on which sixteen models were directly examined. Four dependent variables (Earnings before interest, Taxes, Depreciation and Amortization, Return on Assets, Return on Equity, Assets Turnover Ratio) and eight independent variables (Value Added Intellectual Coefficient, Modified Value Added Intellectual Coefficient, Capital Employed Efficiency, Human Capital Efficiency, Structural Capital Efficiency, Relational Capital Efficiency, Size, and Leverage) were used to form these models. The Empirical Results section has discussed descriptive statistics and correlations, selection of estimate panel data parameter based on the F-statistics, Breusch-Pagan test, and Hausman test, assumption test results (Normality, Autocorrelation, Heteroscedasticity), and panel regression models. Analysis of the impact of VAIC, MVAIC and its elements on the financial performance of Omani industrial companies has yielded mixed results. VAIC and MVAIC in general have a significant positive effect only on ATO. For individual elements of VAIC and MVAIC, the following most significant associations with financial performance measures were found: CEE negatively affects ROE; SCE has a positive effect on l_EBITDA and ATO; RCE negatively affects ATO; l_SIZE has a positive effect on l_EBITDA and ROA; and LEV has a positive effect on ROA.

This paper uses probability method to evaluate the fire safety performance of prestressed steel-concrete beam bridges based on simulation experimental research. Firstly, fire simulation experimental sample analysis was conducted on actual small box girder bridges to obtain the structural response of prestressed steel-concrete structures under fire, which is in line with engineering practice. Next, construct a reliability analysis model for the fire resistance performance of prestressed steel-concrete beam bridges; Combining reliability theory with finite element method, establish a reliability analysis method for the fire resistance performance of prestressed steel-concrete beam bridges. Subsequently, a safety factor evaluation model for the fire resistance performance of prestressed steel-concrete beam bridges was proposed, and a safety factor evaluation method for the fire resistance performance of prestressed steel-concrete beam bridges based on reliability back analysis was established. Finally, based on the analysis of the structural response after a fire in a specific case of a simply supported to continuous prestressed steel-concrete continuous beam bridge project, a structural resistance sample of the prestressed steel-concrete beam bridge is generated through uniform design method, and statistical analysis is conducted. Subsequently, probability methods are used to evaluate the safety of the prestressed steel-concrete beam bridge after a fire. Through analysis, it can be concluded that the time of fire has a significant impact on the structural performance of prestressed steel-concrete beam bridges, and the randomness of parameters has a significant impact on the safety reserve of prestressed steel-concrete beam bridges after fire. It is necessary to pay attention to it in specific engineering practice and strengthen the monitoring and statistics of structural random characteristics.

In this study, three new demountable joints consisting of reinforced concrete columns and steel beams were proposed and their seismic performance was investigated using cyclic loading tests. The test results demonstrated that the three demountable RCS joints had good seismic performance. Using the finite element software ABAQUS, the influence of parameters such as beam flange thickness, bolt strength, and connector steel strength on the seismic performance of each joint was analyzed, and the influence of different parameters on the seismic behavior of the joint was determined. The results also showed that the three demountable RCS joints were sensitive to changes in the thickness of the steel beam flange, while the connector steel strength and bolt type had little impact on the joint's capacity. Additionally, shear capacity calculation formulas for the joint core area provided by different codes and researchers were compared with test and finite element results. The results showed that the calculation results of the ASCE guidance method, the Nishiyama method, and the CECS 347-2013 method were higher than the test values, while the calculation results of the Para method were lower because it did not consider the contribution of the cylindrical steel plate to the shear capacity of the joint core area.

The incorporation of polycarboxylate ether superplasticizer (PCE) type polymer and silica fume (SF) in high-performance concretes (HPC) leads to the achievement of remarkable rheological and mechanical improvements. In the fresh state, PCEs are adsorbed on cement particles and dispersants, in turn promoting the workability of the concrete. Silica fume enables a very well compacted concrete to be obtained, which is characterized by high mechanical parameters in its hardened state. Some PCEs are incompatible with silica fume, which can result in the loss of slump and in poor rheological behavior. The main objective of the research is the study of the influence of three types of PCEs, which all have a different molecular architecture, on the rheological and mechanical behavior of high-performance concretes containing 10% of SF as a partial replacement of cement. The results show that the carboxylic density of PCE has an influence on its compatibility with SF.

The proton exchange membrane fuel cell (PEMFC) is a critical and essential component of zero-emission electro-hydrogen generators. An accurate prediction of its performance is important for optimal operation management and preventive maintenance of these generators. However, the prediction is not simple because the PEMFCs have complex electrochemical reactions with multiple nonlinear relations between operating variables as inputs and voltage as output. In this paper, we propose an efficient prediction approach based on XGBRegressor and Tree-structured Parzen Estimator. In addition, to better select relevant features, Kernel Principal Component Analysis and Mutual Information are jointly used. The proposed approach allows consideration of the dynamic operating conditions of the PEMFC. To test and validate the robustness of the proposed approach, a real data-set of ten PEMFCs was considered. Furthermore, a comparison study with traditional machine learning models, such as artificial neural networks and support vector machine regression, was investigated. The obtained results confirm that our model outperforms the considered traditionel machine learning models.

The UHPC grouted bellow is an innovative technology for connecting assembled buildings, where the anchorage performance of the rebar and UHPC filled in bellows plays a critical role in determining the overall connection effectiveness. To ascertain a dependable anchorage length and establish a bond-slip relationship between the rebar and UHPC within the bellow, we conducted tests on 8 groups of 16 specimens of metal corrugated pipes filled with UHPC and rebar under tension. The tests considered varying parameters such as the aperture ratio D/d and anchorage length L. By analyzing the failure modes, load versus deflection curves, and steel strain data, we gained valuable insights into the influence of the aperture ratio and anchorage length on the anchorage performance. Furthermore, we calculated the experimental curve of the bond-slip relationship between the rebar and the UHPC interface grouted in the bellows and derived a bond-slip model through fitting. These findings serve as a crucial foundation for the force analysis of assembled structures connected using UHPC grouted bellows.

Background: The validation of measuring instruments in health is a requirement to be able to use them safely and reliably. The Short Physical Performance Battery (SPPB) tool is an instrument widely used in the clinic and validated in numerous countries and languages and for different populations. The objective of this research was to determine the psychometric properties of SPPB for a sample composed of institutionalized Spanish older adults. Methods: Multicenter study of the psychometric properties of the Short Physical Performance Battery tool with a convenience sample of 194 institutionalized older adults. Reliability (internal consistency), validity (construct validity and convergent validity) tests were performed. Results: The results show a very good internal consistency, construct validity and convergent validity. In addition, the factorial structure of the SPPB is provided, which reflects that it is a unidimensional scale. Conclusions: In conclusion, the Short Physical Performance Battery is a valid and reliable tool for use with institutionalized older adults. Its use is recommended as part of the Comprehensive Geriatric Assessment for the evaluation of the physical or functional sphere. Authors should include one of the following statements about the registration status of the manuscript here: This study was prospectively registered and approved by the Ethics Committee of the University of Burgos (IR 11/2018).

Marine sediment sample was collected and the total aerobic population was counted and probiotic Bacillus cereus was isolated. Then it was mixed with formulated feed by spraying, while control diet was purchased from a local aquarium. 30 days of feeding experiment was conducted. Carassius auratus fishes were randomly divided into two experimental groups in rectangular tanks. The first group served as a control in which fishes were fed with commercial feed. The second group of fish were fed with probiotic incorporated feed. After 40 days, their survival and growth performance were detected. Bacillus cereus incorporated feed significantly yielded higher survival rate of the fish compared to control. Food conversion ratio (FCR) was significantly lower than the control group. The main aim of this work is to investigate the effect of a marine probiotic bacteria, Bacillus cereus on the survival and growth performance of gold fish Carassius auratus.

The four-way reversing valve is a key component determining whether a heat pump air conditioning system can work. Studying the four-way reversing valve is of great significance for improving the performance of the heat pump air conditioning system. In this paper, the control equation of the sliding block movement process is constructed to simulate the reversing process of the four-way reversing valve in fluid mechanics, and a detailed study is carried out from the sliding block speed, sliding block acceleration, sliding block force, refrigerant leakage, and other aspects. Research has shown that optimizing the structure of the slider can greatly improve the working performance of the four-way reversing valve. Increasing the height of the slider not only improves the pressure relief ability of the four-way reversing valve and prevents the slider from being damaged by high-pressure gas impact, but also reduces the leakage of refrigerant during the directional process; When reducing the length of the slider, although it will improve the pressure relief capacity of the four-way reversing valve, it also increases the amount of refrigerant leakage. The research results provide a theoretical basis and improvement direction for designers to improve the performance of four-way reversing valves.

Redundancy in ship systems is provided to ensure operational resilience through equipment backups which ensures system availability and offline repairs of machinery. The electric power generation system of ships provides the most utility of all systems, hence is provided with good level of standby units to ensure reliable operations. Nonetheless, the occurrence of undesired black outs are common onboard ships and portends a serious danger to ship security and safety. Therefore, understanding the contributing factors affecting system reliability through component criticality analysis is essential to ensure a more robust maintenance and support platform for efficient ship operations. In this regard hybrid reliability and fault detection analysis were conducted to establish component criticality and related fault conditions. A case study was conducted on a ship power generation system consisting of 4 marine diesel power generation plants onboard an Offshore Patrol Vessel (OPV). Results from the reliability analysis indicate overall low system reliability of less than 70 per cent within the first 24 months of the 78 operational months. Component criticality using reliability importance measures was used to identify all components with more than 40 per cent contribution to sub systems failure. Additionally, machine learning was used to aid the reliability analysis through feature engineering and fault identification using Artificial Neural Networks classification. The ANN has identified failure patten threshold at about 200kva which can be attributed to overheating, hence establishing link between component failure and generator performance.

Data security is a fundamental aspect to be considered in Internet of Things (IoT) information gathering systems, as IoT is a network of interconnected devices that collect and share real-time data, becoming increasingly prevalent in our lives. However, data security in IoT systems presents unique challenges due to the large number of devices and access points involved. This study aims to conduct a literature review on IoT security to analyze the performance of security mechanisms on current development platforms, specifically on a Raspberry Pi 3. Some functions from the OpenSSL library were used, including popular hash functions and cipher algorithms. Additionally, a bash code was developed to obtain the time spent in seconds and the memory consumption in kilobytes. In addition to time and memory calculations, statistical values such as variance and standard deviation were also obtained and compared with results obtained on a personal computer. The tests conducted in this study demonstrated that it is possible to implement these algorithms on platforms with more limited resources, with AES and RSA algorithms being the most suitable for IoT scenarios.

In this study, the focus is on the drop test simulation of an MR (Magnetorheological) damper-based main landing gear (MRMLG), aiming to explore multi-degree-of-freedom (DOF) dynamic models during aircraft landing. Three different 6-DOF dynamic models are proposed in this work and their drop performances are compared with results achieved one of commercial softwares. The proposed models include a nonlinear aircraft model (NLAM), a linearized approximated aircraft model (LAAM) linearizing from the nonlinear equations of motion in NLAM, and a fully approximated aircraft model (FAAM) which linearizes the MRMLG's strut force model. In order to evaluate drop performance of the aircraft landing gear system with MR dampers, a 7-DOF aircraft model incorporating the nonlinear MRMLG is formulated using RecurDyn. The principal comparative param-eters are the coefficient of determination (R2) for system response of each model with Re-curDyn model and root mean square error (RMSE) which is the ensembles of CG dis-placement data for each model. In addition, the ensemble of time series data is created for diverse drop scenarios, providing valuable insights into the performance of the proposed drop test models of the aircraft landing gear system featuring MR dampers.

Ce-promoted NiMgAl mixed-oxide (NiCex-C, x = 0, 1,5,10) catalysts were prepared from the quaternary hydrotalcite precursors for CO2 hydrogenation to methane. By engineering the Ce contents, NiCe5-C showed its prior catalytic performance in low-temperature CO2 hydrogenation, being about 3 times higher than that of Ce-free NiCe0-C catalyst (TOF of NiCe5-C and NiCe0-C: 1.19 h-1 vs 0.39 h-1 @ 250 oC). With extensive characterization, it was found that Ce dopants promoted the reduction of NiO by adjusting the interaction between Ni and Mg(Ce)AlOx support. The higest ratio of surface Ni0/(Ni2+Ni0) was obtained over NiCe5-C. Meanwhile, the surface basicity was tailored with Ce dopants. The strongest medium-strength basicity and highest capacity of CO2 adsorption was achieved on NiCe5-C with 5wt% Ce content. The TOF tests indicated a good correlation with medium-strength basicity over the NiCex-C samples. The results showed that the high medium-strength and Ce-promoted surface Ni0 species endows the enhanced low-temperature catalytic performance in CO2 hydrogenation to methane.

The effect of individual and combined supplementation of FA and GPM on physiological variables, productive performance, and carcass characteristics of finishing pigs under heat stress conditions were investigated. Forty Yorkshire x Duroc pigs (80.23 kg) were individually housed and randomly distributed into 4 groups under a 2 x 2 factorial arrangement (n=10): Control (basal diet, BD); FA, BD + 25 mg FA; GPM, BD with 2.5% GPM; and MIX, BD with 25 mg FA and 2.5% GPM. Additives were supplemented for 31 days. The inclusion of FA or GPM did not modify rectal temperature and respiratory rate. An interaction effect (P <0.05) was observed on FI, while average daily gain (ADG) and feed conversion (FC) were not affected by treatments (P >0.05). The inclusion of FA improved hot and cold carcass weight and carcass yields, while the addition of GPM decreased the marbling (P <0.05), and GPM tended to increase loin area (P <0.10). GPM increased liver weight (p <0.05). The addition of GPM and FA can improve some carcass characteristics under heat stress conditions. It is necessary to continue investigating different levels of inclusion of GPM and FA, to demonstrate their potential growth promoting effect in finishing pigs.

The aim of this study was to investigate the impact of Process Oriented Guided Inquiry Learning (POGIL)-based instruction versus lecture-based instruction on Grade 12 students’ performance in circular motion unit. A quasi-experimental, pretest-posttest design, the impact of POGIL-based instruction versus lecture-based instruction on students’ performance as measured by three types of cognitive outcomes: Knowing, Applying and Reasoning (KAR). The total number of participants was approximately 110 students (N=110); 54 were assigned to treatment groups (25 girls and 29 boys) and 56 were assigned to control groups (27 girls and 29 boys). The treatment group was taught a unit of circular motion in physics using POGIL-based instruction while the control group was taught the unit using lecture-based instruction. The findings of the study showed statistically significant differences between students of the control group and the treatment group in favor of the later regarding their circular motion performance, suggesting the superiority of the POGIL in enhancing student understanding of the circular motion.

The problem of health status prediction of insulated-gate bipolar transistors (IGBTs) gains a lot of attention in the field of health management of power electronic equipment. The performance degradation of IGBT gate oxide layer is one of the important failure modes. In view of failure mechanism analysis and easy implementation of monitoring circuit, this paper selects the gate leakage current of IGBT as the precursor parameter of gate oxide degradation, and uses time domain characteristic analysis, gray correlation degree, Mahalanobis distance, Kalman filter and other methods to carry out feature selection and fusion, and finally obtains a health indicator characterizing the degradation of IGBT gate oxide. Based on the Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM) network, this paper constructs an IGBT gate oxide degradation prediction model, and performs experimental analysis on the dataset released by NASA-Ames Laboratory, and the average absolute error of performance degradation prediction is as low as 0.0216. Compared with Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), Support Vector Regression (SVR) and CNN-LSTM models, CNN-LSTM network has the highest prediction accuracy. These results show the feasibility of gate leakage current as a precursor parameter of IGBT gate oxide layer failure, as well as the accuracy and reliability of the CNN-LSTM prediction model.

Environmental regulation has dual effects on water resource utilization performance through various channels such as the "three red lines" and the "Porter hypothesis". Based on the detailed analysis of the impact path of environmental regulation on water resource utilization performance, the two-step system GMM method was adopted to test the dual effects of environmental regulation on water resource utilization performance by using panel data of 30 provinces and cities from 2004 to 2020. The results show that: (1) Environmental regulation has a significant direct impact on water resource utilization performance, and is currently in the stage of positive relationship of an inverted u-shaped relationship. (2) Environmental regulation has a significant indirect impact on water resource utilization Environmental regulation has dual effects on water resource utilization performance through various channels such as the "three-red lines" and the "Porter hypothesis". In accordance with a detailed examination of the influence path of environmental regulation on the performance of water resource utilization, the double effects of environmental regulation on water resource utilization performance were examined using panel statistics from 30 provinces and cities from 2004 to 2020 using the two-step system GMM approach. The results demonstrate that: (1) Environmental regulation has a direct effect on water resource utilization performance which is currently in the stage of the positive relationship of an inverted u-shaped relationship. (2) The influence of environmental regulation on water resource utilization performance through government intervention and industrial structure adjustment is indirect, among which government intervention can significantly improve water resource utilization performance, while the growth of the tertiary industry as a percentage can lower water resource utilization performance. (3) Both direct and indirect impacts indicate that enhancing the efficiency of the use of water resources is sustainable, and the water resource utilization performance of the preceding period had a major positive impact over the present phase. Therefore, the paper sets out a few policy suggestions, such as choosing reasonable environmental regulation tools, actively guiding the market-oriented reform with constraints, and upgrading the industrial structure in a green way.

Water splitting technology is an efficient approach to generate hydrogen (H2) energy, which can well address the problems of environmental deterioration and energy shortage, as well as establishment of a clean and sustainable hydrogen economy powered by renewable energy sources due to the green reaction of H2 with O2. While the efficiency of H2 production by water splitting technology is intimately related with the reactions on electrode. Nowadays, the efficient electrocatalysts in water splitting reactions are the precious metal-based materials, i.e., Pt/C, RuO2 and IrO2. Ni (Co, Fe)-based layered double hydroxides (LDH) 2D materials are the typical non-precious metal-based materials in water splitting with advantages of low cost, excellent electrocatalytic performance and simple preparation methods, which exhibits a great potential for the substitution for precious metal-based materials. This review summarizes the recent progress of Ni (Co, Fe)-based LDH 2D materials for water splitting, which mainly focuses on discussing and analyzing the different strategies to modify LDH materials towards high electrocatalytic performance. We also discuss the recent achievements including their electronic structure, electrocatalytic performance, catalytic center, preparation process and catalytic mechanism. Furthermore, the characterization progress in revealing electronic structure and catalytic mechanism of LDH is highlighted in this review. Finally, we put forward some future perspectives related to design and explore advanced LDH catalysts in water splitting.

One of the influential factors in estimating the service life of reinforced concrete bridges (RCB) is determining the long-term seismic performance of these structures. Corrosion due to chloride ion diffusion leads to the destruction of critical members of the RCB during the useful life of the structure. So, the long-term seismic performance of the bridge deteriorates as a result. It is essential to study the effect of corrosion deterioration on the long-term seismic performance of bridges in the southern regions of Iran, near the coasts of the Persian Gulf and the Oman Sea, because of the seismicity of the region and high corrosion rate of reinforced concrete (RC) members is the result of environmental conditions. In order to investigate this issue, considering studies about environmental conditions of southern Iran, the onset time of corrosion in the columns, as seismic critical members of the bridge, was determined. Based on that, the corrosion's effect on characteristics of RC at specific time points during the bridge's useful life (0, 15, 30, 45, 60, 75 and 90 years) have been calculated. The effects of corrosion include deterioration of the core and cover concrete properties, steel bar and the connection between concrete and steel bar. In the next step, at each time point, according to the modified stress-strain relationships, the moment-curvature analysis of the bridge pier was done, and the properties of the plastic hinge were determined. Finally, based on the obtained data about plastic hinge characteristics at each time point, overload analysis of the bridge was performed in both longitudinal and transverse directions. Then the capacity curves of RCB were compared at the mentioned time-points. The results show that the capacity of the bridge deteriorates over time due to corrosion. Therefore, a proposal to increase the value of base shear design has been made to ensure the long-term seismic performance of RCB in corrosive environments.

The year 2022 was characterized by several major events that impacted the business world in Indonesia and even globally after the COVID-19 pandemic devastated all business sectors in Indonesia and the world. The current business environment is experiencing accelerating turbulence characterized by increasing intensity of business competition, rapid changes in the market, and industrial connections climate. The industrial connection climate of an institution can be measured by the pattern of relationships that occur between workers and management. Industrial connections are fundamental to the sustainability of an organization and are understood as an important factor in influencing institutional performance. This research aims to look at the impact of the existence of industrial connections instruments, turbulence in the business environment on the industrial connections climate. Besides, how the industrial connections climate relates to firm performance. The research design is an inferential quantitative, using sampling and snowball sampling methods with total sample are 406. The data collected were analyzed using Structural Equation Model using LISREL version 8.70. This research used a survey to build an SEM model that tested the effect of organizational turbulence and industrial connections instruments on organizational climate directly, and tested mediation on organizational performance. All related indicators have outer loading more than 0.5 and T-value more than 1.96. Therefore, the conclusion is that all measurements are valid. Composite Reliability (CR) and VE for all indicators are >0.7 and >0.5 respectively. This research shows that industrial assosiation climate has a positive effect on business turbulence and industrial connections instruments. However, industrial connections instruments show a greater impact on the assosiation climate. This is because industrial connections instruments are the media used in the implementation of industrial connections in organizations. This research also confirms that industrial assosiation climate is positively related to organizational performance. The result of the indirect influence (IE) of 0.20 with t value is 8.47 means that the climate of Industrial connections is able to mediate the influence of Industrial connections Facilities on Organizational Performance.

Previous research has either neglected to consider misbehaviour or misconduct in the virtual workplace during the current COVID-19 pandemic or highlighted some challenges encountered with remote working or work from home but in isolation, e.g., misbehaviours or ethical concerns associated with improper use of technology when accessing clients’ confidential information, without understanding their aetiology and context in a holistic manner. This has impacted the ability of existing research in providing recommendations organisations can practically implement to improve the sustainability and productivity of the virtual workplace, especially as they seek to navigate the current pandemic and prepare for the global business environment in the next decade. Instead, this study, for the first time, proposes a novel holistic methodology to identify the aetiologies of ethical and performance challenges with focus to the Information Technology consulting sector, as well as developing a set of recommendations companies can adopt to manage such behavioural and productivity challenges. Thus, this study illustrates the key issues associated with remote working implemented to respond to the current COVID-19 pandemic, which mine not only the individual performance in an organisation but also its overall productivity, as well as suggests the main performance and reward management strategies that can be leveraged to mitigate them. Tailored strategies are described and discussed as referred to this industry to help in navigating a more unstable yet competitive market to manage the virtual employees’ misbehaviours in the workplace and drive growth for individuals and organisations alike.

Purpose: This research aims to model a police agency ordering problem based on criteria that measure the performance of operational and logistical variables, using a multicriteria method. Design/methodology/approach: The multicriteria method PROMETHEE II was used, which with the aid of the Visual PROMETHEE software, emulated the systematized data in the impact matrix and produced the final ordering of the most efficient police agencies in equalizing the operational, logistical, financial, and human resources applied in the combating crime and reducing criminal indices. Findings: The results confirmed that the resources made available to police agencies located in different municipalities in the metropolitan region of the state of Rio de Janeiro are better applied by managers compared to police units in the capital of Rio de Janeiro. Research limitations/implications: As implications of the research, it can be inferred that the use of multicriteria methods in modelling problems in ​​public security can contribute to the rationalization of the use of available resources to fight crime in large cities. Research has shown that it is possible to use the multicriteria methodology in ordering police agencies that best equalize the available resources. Practical implications: The practical impact of this research lies in optimizing the resources available to law enforcement agencies in the fight against crime in general. Social implications: The results can influence the decision making of the local government in the allocation of resources, as well as offering sectors of the economy information relevant to local development. Originality/value: The results of the MCDA analysis can be used to help police agencies in Rio de Janeiro, Brazil to be more efficient. In addition, the application of MCDA can be a new approach to measuring the efficiency of police services.

Tobamovirus species represent a threat to solanaceous crops worldwide, due to their extreme stability and being seed-borne. In particular, recent outbreaks of tomato brown rugose fruit virus in tomato and pepper crops led to the establishment of prompt control measures, and the need for reliable diagnosis was urged. Another member of the genus, tomato mottle mosaic virus, has recently risen attention due to reports in different continents and its common features with tomato brown rugose fruit virus. In this study, a new real-time RT-PCR detection system was developed for tomato brown rugose fruit virus and tomato mottle mosaic virus on tomato leaves and seeds using TaqMan chemistry. This test was designed to detect tomato mottle mosaic virus by amplifying the movement protein gene in a duplex assay with tomato brown rugose fruit virus target on the CP-3’NTR region, which was already validated as a single assay. The performance of this tests was evaluated, displaying analytical sensitivity 10-5-10-6-fold dilution for seeds and leaves, respectively, and good analytical specificity, repeatability, and reproducibility. Using the newly developed and validated test, tomato brown rugose fruit virus detection was 100% concordant with previously performed analyses on 106 official samples collected in 2021 from different continents.

As a potential motivation, psychological empowerment stimulates employees' work behaviors, and it determines the degree of effort and duration of employees' work. Only when employees are psychologically empowered, will they have an impact on their behavior when they believe that they are trusted. This paper chose to set the independent variable as the employee's perceived trust and the dependent variable as the company's work performance, and explored the mediating role of psychological empowerment in the two. The psychological empowerment of employees had a positive impact on work performance. Employees with high psychological empowerment tended to be proactive in their work, and had more input in the work, which in turn encouraged employees to have higher work performance. The four dimensions of psychological empowerment can positively affect employee task performance, and the ability and influence of psychological empowerment had a positive impact on relationship performance. Psychological empowerment as a whole perception played a part of the mediating role between the perception of superior dependency and task performance, and it played a part of the mediating role between perception of superior dependency and relationship performance. As a whole perception, psychological empowerment played a part of mediating role between perceived information disclosure and task performance, and part of mediating role between perceived information disclosure and relationship performance. In the study of perceived trust and work performance, this article focused on the mediating role of psychological empowerment, and further understood the internal mechanism of perceived trust.

The circumstances arising from the exceptional situation caused by the COVID-19 pandemic have affected all socioeconomic areas in the last two years. The field of Education has not been an exception and the management of the situation seems to have caused an increase in the level of perceived stress of university students. On this basis, this research that aims, first, to analyze the student’s level of perceived stress during the de-escalation and return to normality period, secondly, to evaluate its relationship with life satisfaction and, finally, to detect the students' needs in stress management, has been developed. An exploratory-descriptive study of quantitative and cross-sectional nature has been carried out. 222 university students of the Childhood and Primary Education Degrees of the University of Jaén (Spain) have participated. The instruments, Perceived Stress Scale (PSS) and Satisfaction with Life Scale (SWLS) have been used. The results show a moderate and partial relationship among the dimensions of the used instruments. The obtained coefficients of determination are, Academic Performance (r² = .019) and Life Satisfaction (r² = .402), with a mean square error (SRMR) of .079. These findings show the need to develop actions within the university training program in effective stress management strategies.

This paper seeks to optimize the mechanical and durability properties of ultra-high performance concrete (UHPC). To meet this objective, concrete specimens were manufactured by using 1,100 kg/m3 of binder, water/binder ratio 0.20, silica sand and last generation of superplasticizer. Silica fume, metakaolin and two types of nano silica were used for improving the performances of the concrete. Additional mixtures included 13mm long OL steel fibers. Compressive strength, electrical resistivity, mercury intrusion porosimetry tests and differential and thermogravimetric thermal analysis were carried out. The binary combination of nano silica and metakaolin, and the ternary combination of nano silica with metakaolin and silica fume, led to the best performances of the UHPC, both mechanical and durable performances.

An increasing number of studies have shown that safety culture factors have a substantial influence on safety performance in a variety of industrial sectors. These factors' impact on safety performance is unclear, especially at the public service and statutory authorities. On the other hand, the understanding of indicators for safety performance in every working sector in Malaysia is on the continuing progress. Hence, this study's contribution is to explore the influence of safety culture factors (i.e., management commitment and supervision in safety, safety system) and safety competence on safety performance in government paramedic training institutes. IPMA (importance-performance map analysis) is a technique used in Smart PLS to determine the significance and performance of each of these factors. The study was conducted via an online survey and involved 258 safety and health committee members in Ministry of Health paramedic training institute. As a matter of relevance, the IPMA's empirical data study revealed that management commitment and supervision in safety were the predominant factors in determining safety performance. Meanwhile, for performance, the findings showed that worker involvement, safety system, and safety competence perform well in determining the safety performance.

This overview study set out to compare and synthesise the findings of review studies conducted on predicting student academic performance (SAP) in higher education using educational data mining (EDM) methods, EDM algorithms and EDM tools from 2013 to June 2020. It conducted multiple searches for suitable and relevant peer-reviewed articles on two online search engines, on nine online databases, and on two online academic social networks. It, then, selected 26 eligible articles from 2,050 articles. Some of the findings of this overview study are worth mentioning. First, only 2 studies explicitly stated their precise sample sizes with maths and science as the two most mentioned subject areas. Second, 16 review studies had purposes related to either EDM techniques, EDM methods, EDM models, or EDM algorithms employed to predict SAP and student success in the higher education sector. Third, there are six commonly used typologies of input variables reported by 26 review studies, of which student demographics was the most commonly utilised variable for predicting SAP. Fourth and last, seven common EDM algorithms employed for predicting SAP were identified, of which Decision Tree emerged both as the most used algorithm and as the algorithm with the highest prediction accuracy rate for predicting SAP.

Based on the Organizational Support Theory, this study examines the relationship between human resource management practices and service performance of sharing workers by demonstrating the mediation role of work engagement. We tested this theoretical model using an in-person interview questionnaire survey of 318 downwind drivers. Results showed that: (1) the main effect of human resource management practices of sharing workers on service performance was significant; (2) work engagement played a prominent mediation role between human resource management practices and service performance of sharing workers; (3) the mediation role of employee vigor between the platform incentives and the performance of employee services was significant; (4) employee dedication had an obvious and indirectly positive mediating effect between sharing workers' dimensions of human resource management practice and their service performance; (5) employee absorption on the mediation role between the various dimensions of the sharing human resources management practices (platform support, platform incentives and platform constraints) and employee service performance was significant. This study has important value for the study on human resource management practices in the context of sharing economy, and provides practical enlightenment for employee management of the sharing economy platform.

While appropriate nutrient intake is important for older adults, various oral problems cause de-creased masticatory function. This cross-sectional study aimed to identify the factors associated with decreased masticatory performance in older adults. Oral examinations were performed on 80 participants (mean age: 75.10 ± 5.64 years) to determine the number of functional tooth units (FTUs). Symptoms of periodontal and temporomandibular diseases were evaluated via a ques-tionnaire. The tone, elasticity, and dynamic stiffness of the masseter muscle were measured using the Myoton® PRO device. The mixing ability test was used to assess the masticatory performance and the mixing ability index (MAI) was calculated. The analysis of covariance test was performed to adjust for confounding factors and multiple logistic regression analysis was performed to identify the risk factors affecting MAI. A lower MAI was significantly associated with higher tone (p = 0.006) and lower elasticity (p = 0.013). The number of FTUs (adjusted odds ratio [OR] = 0.724, p = 0.029), tone (adjusted OR = 1.215, p = 0.016), and elasticity (adjusted OR = 4.789, p = 0.038) were independently associated with the MAI. Muscle function training and prosthetic treatments may help increase masticatory performance in older adults, which will improve overall health.

(1) Background: The diphtheria toxoid antigen is a major component in pediatric and booster combination vaccines and is known to raise a protective humoral immune response upon vaccination. Although antibodies are considered critical for diphtheria protection, little is known about the antigenic determinants that maintain humoral immunity. (2) Methods: One hundred twelve 15-mer peptides covering the entire sequence of DTx protein were prepared by Spot-synthesis. Membrane-bound peptides immunoreactivity with sera from mice immunized with triple DTP vaccine allowed mapping of continuous B-cell epitopes, topological studies, MAPs synthesis, and ELISA development. (3) Results: Twenty epitopes were identified, being 2 in the signal peptide, 5 in the CD, 7 in the HBFT domain, and 5 in the RBD. Two 17-mer (CB/Tx-2/12 and CB/DTx-4-13) derived bi-epitope peptides linked by a Gly-Gly spacer were chemically synthesized. The peptides were used as antigens to coat ELISA plates and assayed with human (huVS) and mice vaccined sera (miVS) for in vitro diagnosis of diphtheria. The assay proved to be highly sensitive (99.96%) and specific (100%) either for huVS and miVS and when compared with a commercial ELISA test, demonstrate high performance. (4) Conclusions: Our work displayed the complete picture of the linear B cell IgG response epitope of the DTx responsible for the protective effect and demonstrated the specificity and eligibility to enter phase IIB studies of some epitopes to develop new and fast diagnostic assays.

Arbutus unedo L. is a small Ericaceae tree with a circum-Mediterranean distribution. It has a huge ecological impact on southern Europe forests and a great economic importance, as a source of phytochemicals with bioactive properties and for fruit production. On the foreseen climate change context, breeding towards drought tolerance is necessary in order to ameliorate plant performance. The aim of this work was therefore to study the reproduction mechanisms of strawberry tree, obtain new genetic combinations by hybridization and select genotypes more tolerant to drought stress. A morphological analysis of flowers and pollen was carried out, and controlled pollinations performed both in vitro and ex vitro. The very first approach on strawberry tree breeding by means of hybridization is also presented. Several physiological parameters were evaluated on 26 genotypes submitted to a water deficit regime. Plant behavior under drought greatly varied among genotypes, which showed a high phenotype plasticity. Three genotypes that were able to cope with water restriction without compromising net CO2 assimilation were identified as highly tolerant to drought stress. The results obtained elucidate the reproduction mechanisms of strawberry tree and open the way for a long-term breeding program based on the selection of drought tolerant plants.

COVID-19 pandemic will continue to pose a major public health threat until vaccination-mediated herd immunity is achieved. Most projections predict vaccine will reach a large subset of the population late in 2021 or early 2022. In the meantime, countries are exploring options to remove strict lockdown measures and allow for society and the economy to return to normal function. One possibility is to expand on existing COVID-19 testing strategies by including large-scale rapid point of care diagnostic tests (POCTs). Currently, there is significant variability in performance and features of available POCTs, making selection and procurement of appropriate test for specific use case difficult. In this review, we have used the World Health Organization’s (WHO) recently published Target Product Profiles (TPPs) for specific use cases of COVID-19 diagnostic tests to screen for top-performing POCTs on the market. Several top-performing POCTs, based on clinical sensitivity/specificity, the limit of detection, and time to results, that meet WHO TPP criteria for direct detection of SARS-CoV-2 (acute infection), or indirect diagnosis of past infection (host antibodies) are highlighted here.

This study was conducted to propose the Green Economic Development Plan for Manufacturing S.M.E.s based on financial performance and operations thru Green Initiatives. The descriptive survey method used to gather data to determine the green initiative's implementation of small and medium (S.M.E.s) manufacturing enterprises. Green initiatives use as a basis for crafting a green economic development plan. Document analysis was also employed to obtain data from any available printed materials and records provided by the respondents. Such methods of gathering information used to validate data gathered from local and foreign-related literature. The observation also employed to survey the assets owned and validate any green initiatives practiced, including their implementation. The study's findings show that among the green initiatives implemented by SMMEs, which resulted in the reduction of total costs and expenses, were the proper disposal and segregation of waste materials, water management by recycling wastewater and using water-efficient equipment, natural resources, and raw materials management. SMMEs should encourage active participation and support of suppliers and customers in achieving G.E.D.'s objectives by developing incentive schemes.Furthermore, SMMEs should continue to benchmark with G.E.D. Practitioners are operating locally and abroad to adopt best greening strategies and regularly network with concerned government agencies for continuous updating on G.E.D. Initiatives that may benefit the firm. Further research may be conducted on green initiatives implemented by small and medium enterprises in other industry sectors.

A novel polyphenol‑coated CoFe₂O₄ system was synthesized as a magnetic adsorbent by chemical oxidative polymerization process for magnetic solid-phase extraction of lawsone. The synthesized nanoadsorbent showed a spherical morphology with diameters under 50 nm by scanning electron microscopy images. The extraction efficiency of this adsorbent was studied towards the extraction of lawsone from saline aqueous solution in dispersion mode. Major parameters including the type and volume of desorption solvent, amount of sorbent, desorption time, extraction time, extraction temperature, ionic strength and pH were optimized. Under the optimum conditions the relative standard deviation in 0.005 µg mL^-1 (inter-day n = 6; intra-day: n = 6; and adsorbent to adsorbent n = 4) were obtained as 5.2, 8.07 and 11.7%, respectively. A linear calibration curve in the range of 0.003–0.5 µg mL^-1 with R² = 0.993 was obtained. The limit of detection and limit of quantification of the method were 0.001 µg mL^-1 and 0.003 µg mL^-1, respectively. The relative recovery percentages were in range of 90-96.4% for henna leaves, henna shampoo, and henna dermal lotion real samples.

Three-dimensional (3D) facies and petrophysical models were generated from previously published data of carbonate strata in the Dam Formation (eastern Saudi Arabia) to quantitatively investigate, describe, understand, model, and predict the permeability anisotropy of tidal flat carbonate within a sequence stratigraphic framework. The resulting 3D models were used to conduct fluid flow simulations to demonstrate how permeability anisotropy influences the production of hydrocarbons and ultimately affects decisions concerning future drilling in the exploration and development of carbonate reservoirs that have tidal flat strata. The constructed 3D facies model consists of four lithofacies associations, two of which were grain-dominated associations and two of which were mud-dominated associations. These lithofacies associations varied spatially in four reservoir zones (zones 1 to 4), which represent two fourth-order sequences in the uppermost part of the Dam Formation. Zones 1 and 3 consist of transgressive parasequences, and zones 2 and 4 consist of the regressive parasequences of these sequences. The 3D porosity and permeability models have a coherent match with the distribution of the lithofacies and the stratigraphic framework of the Dam Formation. The results suggested that the permeability anisotropy in zones 1 and 3 is controlled by the occurrence of the grain-dominated lithofacies associated with tidal flat channels. This lithofacies association overlies the sequence boundaries of sequences 1 and 3, forms reservoir bodies with relatively high permeability values, and is elongated perpendicular to the shoreline of the depositional environments. In contrast, permeability anisotropy in zones 2 and 4 is thought to be controlled by the occurrence of the grain-dominated lithofacies associated with the oolitic shoal. This lithofacies association overlies the maximum flooding surface of sequences 2 and 4, forms reservoir bodies with relatively high permeability values, and is elongated parallel to the shoreline of the depositional environments. Fluid flow simulation results suggested that the trend in hydrocarbon production from the constructed 3D models depends on permeability anisotropy in each reservoir zone. Thus, recognizing trends in permeability anisotropy, which might be predicted using sequences stratigraphy, could help to identify potential areas for future drilling.

This paper incorporates the definition of Intrusion Detection Systems and the methodologies utilised by these systems. As well as this, this research paper also encompasses a taxonomy and a survey of IDS and the specific strategies and principles. Finally, this paper also includes a discussion amongst other authors for instance what the authors differ and agree on, along with the previously related studies.

In this paper we show how to efficiently implement parallel discrete simulations on Multi-Core and GPU architectures through a real example of application: a cellular automata model of laser dynamics. We describe the techniques employed to build and optimize the implementations using OpenMP and CUDA frameworks. We have evaluated the performance on two different hardware platforms that represent different target market segments: high-end platforms for scientific computing, using an Intel Xeon Platinum 8259CL server with48cores and also an NVIDIA Tesla6V100 GPU, both running on Amazon Web Server (AWS) Cloud, and on a consumer-oriented platform, using an Intel Core i9 9900k CPU and an NVIDIA GeForce GTX 1050 TI GPU. Performance results are compared and analysed in detail. We show that excellent performance and scalability can be obtained in both platforms, and we extract some important issues that imply a performance degradation for them. We also found that current Multi-Core CPUs with large core numbers can bring a performance very near to that of GPUs, even similar in some cases.

When discussing the concepts of risk, safety, and security, people have an intuitive understanding of what these concepts mean, and, to a certain level, this understanding is universal. However, when delving into the real meaning of these concepts, one is likely to fall into semantic debates and ontological discussions. In industrial parks, it is important that (risk) managers from dierent companies, belonging to one and the same park, have the same understanding of the concepts of risk, safety, and security. It is even important that all companies in all industrial parks share a common understanding regarding these issues. As such, this paper explores the similarities and dierences behind the perceptions of these concepts, to come to a fundamental understanding of risk, safety, and security, proposing a semantic and ontological ground for safety and security science, based on an etymological and etiological study of the concepts of risk and safety. The foundation has been induced by the semantics used in the ISO 31000 risk management guidance standard. Hence, this article proposes a coherent, standardized set of concepts and definitions with a focus on the notion “objectives” that can be used as an ontological foundation for safety and security science, linking “objectives” with the concepts of safety, security, risk, performance and also failure and success, theoretically allowing for an increasingly more precise understanding and measurement of (un)safety across the whole range of individuals, sectors and organizations, or even society as a whole.

Polyvinyl alcohol-engineering cementitious composites (PVA-ECC) has been widely applied in bridge deck repairing or widening, the common practice for doing this is that a portion of a bridge is left open to traffic while the closed portion is constructed, which expose the early age PVA-ECC to the vehicle-induced vibrations. However, whether vehicle-induced vibrations affect the tensile performance of early age PVA-ECC remains unknow. The purpose of this study was to conduct laboratory test programs on how much vehicle-induced vibrations during early ages affected the tensile performance of PVA-ECC. A self-improved device was used to simulate the vehicle-induced vibrations, and after vibrating with the designed variables, both a uniaxial tensile test and a grey correlation analysis were performed. The results indicated that: the effects of vehicle-induced vibrations on the tensile performance of early age PVA-ECC were significant, and they generally tended to be negative in this investigation. In particular, for all of the vibrated PVA-ECC specimens, the most negative age when vibrated occurred during the period between the initial set and the final set. We concluded that although vehicle-induced vibrations during the setting periods had no substantial effects on the inherent strain-hardening characteristics of PVA-ECC, the effects should not be ignored.

Opportunistic routing is the latest technique that uses the broadcasting nature of the wireless medium to increase the number of potential forwarding nodes in the network. This, in turn improves the delivery rate and reliability of data transmission in the network. Compared to all previous classes of routing protocols, opportunistic routing offers numerous advantages which is exploited by the latest applications for efficient communication and resource sharing in dynamic ad hoc networks. These applications provide dynamic communication in disaster recovery environments. The objective of this research work is to review and classify all the major opportunistic routing protocols proposed for dynamic ad hoc networks. Further the issues and challenges with each of these existing protocol is discussed and future research directions are put forward

For the task planning problem of the command and control architecture, the existing algorithms have problems such as low efficiency and poor re-planning quality under abnormal conditions. Based on the requirements of the current accusation architecture, this paper constructs a distributed command and control architecture model based on multi-agents, which makes use of the superiority of multi-agents in dealing with complex tasks. The concept of MultiAgents-HTN is proposed under the framework. The original hierarchical task network planning algorithm is optimized, the multi-agent collaboration framework is redefined, and the coordination mechanism of local conflict is designed. Taking the classical resource scheduling problem as the experimental background, the comparison between the proposed algorithm and the classical HTN algorithm is carried out. The experimental results show that the proposed algorithm has higher quality and higher efficiency than the existing algorithm, and the space anomaly is heavy during processing. The planning is more efficient, and the time is more complicated and superior in dealing with the same problem, with good convergence and adaptability. The conclusion proves that the distributed command and control architecture proposed in this paper has high practicability in related fields and can solve the problem of distributed command and control architecture in multi-agent environment.

Opportunistic routing uses the broadcasting nature of the wireless medium to increase the number of potential forwarding nodes in the network. This, in turn improves the delivery rate and reliability of data transmission in the network. Compared to all previous classes of protocols, opportunistic routing offers numerous advantages which is exploited by the latest applications for efficient communication and resource sharing in dynamic ad hoc networks. The objective of this research work is to review and classify all the major opportunistic routing protocols proposed for dynamic ad hoc networks. Further the issues and challenges with each of these existing protocol is discussed and future research directions are put forward.

Opportunistic Routing is a promising paradigm that has been proposed for efficient and reliable transfer of data packets in mobile ad hoc networks. This routing strategy takes advantage of the broadcasting nature of the wireless medium to increase the number of probable forwarding devices and improves the reliability of data transfer in the network. Opportunistic Routing utilizes the reception of the same broadcasted packet at multiple devices in the network and selects one best forwarder dynamically from the set of multiple receivers. A number of opportunistic routing protocols have been proposed over these years for effective data delivery in ad hoc networks. But as the speed and mobility of devices increases in the network, performances of the existing opportunistic routing protocols degrade considerably, leading to reduced Quality of Service and poor transmission efficiency. The exceptional potential of opportunistic routing is thus underutilized. In this research we introduce Optimized Opportunistic Routing (OOR) strategy that guarantee excellent Quality of Service and high transmission efficiency to the latest applications using opportunistic routing for communication in highly dynamic ad hoc networks. Simulation results show that our method achieve significant performance improvements compared to all other existing opportunistic routing protocols in highly dynamic mobile ad hoc networks.

This study aims to determine the optimal configuration (position and operation duration) for wall mounted mechanical mixers based on the comparison of three-dimensional computational fluid dynamics (CFD) modelling results and physical data collected from the treatment plant. A three-dimensional model of anoxic zone 1, 2 and 3 of Northern Wastewater Treatment Plant (WWTP) located at Cairns Regional Council, Cairns, Queensland, Australia was developed and validated. The model was used to simulate the flow pattern of the WWTP and the simulation results are in good agreement with the physical data varying between 0% to 15% in key locations. The anoxic zones were subject to velocities less than the desired 0.3 metres per second however results for suspended solids concentration indicate that good mixing is being achieved. Results for suspended solids concentrations suggest that the anoxic zones are towards the upper limits recommended by literature for specific power dissipation. The duration for operation of mechanical mixers was investigated and identified that the duration could be reduced from 900 seconds down to 150 seconds. Alternative mixer positioning was also investigated and identified positioning which would increase the average flow velocity with decreased duration (150 seconds). The study identified that Council may achieve savings of $24,000 per year through optimisation of the mechanical mixers.

In this study, the on-going research into the improvement of micro-gas turbine propulsion system performance and the suitability for application as propulsion systems for small tactical UAVs (<600 kg) is investigated. The study is focused around the concept of converting existing micro turbojet engines to turbofan with the use of a continuously variable gearbox, thus maintaining a single spool configuration and relative design simplicity. This is an effort to reduce the initial engine development cost, whilst improving propulsive performance. The BMT 120 KS micro turbojet engine is selected for performance evaluation of the conversion process using gas turbine performance software, GasTurb13. The preliminary design of a matched low-pressure compressor (LPC) for the proposed engine is then performed using meanline calculation methods. According to the analysis carried out, an improvement in the converted micro gas turbine engine performance in terms of thrust and specific fuel consumption is achieved. Furthermore, with the introduction of a CVT gearbox, fan speed operation may be adjusted independently of the core, allowing increased thrust generation or better fuel consumption. Therefore, enabling a wider gamut of operating conditions and enhances the performance and scope of tactical UAV.

Three-temperature heating systems consist of a heat engine and a heat pump, enabling thus maximum usage of the primary thermal source for the heating of buildings. This analysis has revealed obvious advantages and disadvantages that the combining of thermodynamic systems has in future development, also with respect to environmental and economic issues. It appears that the combination of a Stirling engine or a similar heat drive with a heat pump is especially suitable. In order to analyze the effectiveness of such a system, a comprehensive calculation procedure is used: its basis lies in accounting for all types of energy and their relationship to the original natural resource. The present paper aims to point out that the combination of Stirling engine and a heat pump is a useful solution thanks to the most favorable resultant economic impact if compared to the usage of a diesel, four-stroke gas, or, most commonly used, electric drive.

The performance evaluation of the Internet of Things (IoT) based supply chain is challenging due to the involvement of multiple decision makers, the multi-dimensional nature of the evaluation process, and the existence of uncertainty and imprecision in the decision making process. To ensure effective decisions are made, this paper presents a fuzzy multicriteria analysis model for evaluating the performance of IoT based supply chain. The inherent uncertainty and imprecision of the performance evaluation process is adequately handled by using intuitionistic fuzzy numbers. A new algorithm is developed for determining the overall performance index for each alternative across all criteria. The development of the fuzzy multicriteria group decision making model provides organizations with the ability to effectively evaluate the performance of their IoT based supply chains for improving their competitiveness. An example is presented for demonstrating the applicability of the model for dealing with real world IoT-based performance evaluation problems.

Physical frailty and sarcopenia (PF&S) are hallmarks of aging that share a common pathogenic background. Perturbations in protein/amino acid metabolism may play a role in the development of PF&S. In this preliminary study, 68 community-dwellers aged 70 years and older, 38 with PF&S and 30 non-sarcopenic, non-frail controls (nonPF&S), were enrolled. A panel of 37 serum amino acids and derivatives was assayed by UPLC-MS. Partial Least Squares Discriminant Analysis (PLS-DA) was used to characterize the amino acid profile of PF&S. The optimal complexity of the PLS-DA model was found to be three latent variables. The proportion of correct classification was 76.6 ± 3.9% (75.1 ± 4.6% for enrollees with PF&S; 78.5 ± 6.0% for controls). Older adults with PF&S were characterized by higher levels of asparagine, aspartic acid, citrulline, ethanolamine, glutamic acid, sarcosine, and taurine. The profile of nonPF&S individuals was defined by higher levels of α-aminobutyric acid and methionine. Distinct profiles of circulating amino acids and derivatives characterize older individuals with PF&S. The dissection of these patterns may provide novel insights into the role played by protein/amino acid perturbations in the disabling cascade and possible new targets for interventions.

In this article, management control has been studied from the perspective of intention towards sustainable development of companies. The main idea focuses on the analysis of relations between sustainable management control and the system of performance appraisal using as a reference the resource-based theory. These relations have been assessed both theoretically by reviewing literature in the field, and empirically based on data collected in a questionnaire from top management, as well as data from Annual Reports from the main segment of Bucharest Stock Exchange. The authors have shown that financial performance has a significant influence on management control, and the return on capital employed is one of the most recommended indicators. The sustainable nature attributed to management control is the result of institutional theory evolution, provisions of Directive 2014/95/EU and Guide of Global Management Accounting Principles (2015) using stewardship. Consequently, profits are not the main element any more in the assessment of financial „health” of a company. To ensure the sustainable success, sustainable balanced scorecard is one of real measures for managing financial and non-financial performance.

Wind turbine upgrades have been spreading in the recent years in the wind energy industry, with the aim of optimizing the efficiency of wind kinetic energy conversion. This kind of interventions has material and labor costs and it is therefore fundamental to estimate realistically the production improvement. Further, the retrofitting of wind turbines sited in harsh environments might exacerbate the stressing conditions to which wind turbines are subjected and consequently might affect the residue lifetime. This work deals with a case of retrofitting: the testing ground is a multi-megawatt wind turbine from a wind farm sited in a very complex terrain. The blades have been optimized by installing vortex generators and passive flow control devices. The complexity of this test case, dictated by the environment and by the features of the data set at disposal, inspires the formulation of a general method for estimating production upgrades, based on multivariate linear modeling of the power output of the upgraded wind turbine. The method is a distinctive part of the outcome of this work because it is generalizable to the study of whatever wind turbine upgrade and it is adaptable to the features of the data sets at disposal. In particular, applying this model to the test case of interest, it arises that the upgrade increases the annual energy production of the wind turbine of an amount of the order of the 2%. This quantity is of the same order of magnitude, albeit non-negligibly lower, than the estimate based on the assumption of ideal wind conditions. Therefore, it arises that complex wind conditions might affect the efficiency of wind turbine upgrades and it is therefore important to estimate their impact using data from wind turbines operating in the real environment of interest.

In reservoir engineering, one of the main sources of information for the characterization of reservoir and well parameters is well testing. Among the unconventional well testing methodologies, Harmonic Well Testing (HPT) is appealing from an economic standpoint because it could provide well performance and reservoir behavior monitoring without having to interrupt field production. Recorded pressure analysis is performed in the frequency domain by adopting a derivative approach similar to conventional well testing. To this end, pressure and rate data must be decomposed into harmonic components. Test interpretability can be significantly improved if pressure data are detrended prior to interpretation, filtering out non periodic events such as discontinuous production from neighboring wells and flow regime variations which did not respect the designed test periodicity. Therefore, detrending offers the possibility of overcoming the limitation of HPT applicability due to the difficulty of imposing a regularly pulsing rate for the whole test duration (typically lasting several days). This makes HPT attractive for well performance monitoring, especially in gas storage fields. In this paper, the application of different detrending methodologies to synthetic HPT pressure data generated in different reservoir and operational scenarios is presented and discussed. Moreover, a real case application is also presented.

A lack of trust in Energy Service Company (ESCo) is the most critical factor affecting the development of Energy Performance Contracting (EPC) in China compared with other constraints. One cannot easily estimate the energy-saving performance of an EPC project. Under that condition, lack of trust may cause the Energy-Consuming Unit (ECU) to suspect the energy-saving performance promised by the ESCo, thus leaving potentially profitable projects without necessary funding. Currently, specific studies taking an across-projects viewpoint on annual energy-saving performance of EPC projects in multiple subsectors objectively and quantitatively are lacking. This paper studies the regression relationships of annual energy-saving quantity in terms of revamping cost and the regression relationships of annual cost saving in terms of revamping cost. The regression results show that there are statistically significant correlations in the above relationships in the nine subsectors investigated. This is significant for ESCos and ECUs because knowledge on energy-saving performance could contribute to EPC investment decisions and trust relationships between ESCos and ECUs. Then a multiple linear regression model of revamping cost is set up to analyze its influencing factors. The model indicates that the subsector the sample belongs to, financing, registered capital of the ESCo, and contract period have significant effects on revamping cost. Thus, policy implications regarding innovation of EE promotion technology, clarifying ESCos’ exit mechanism, innovation of financing mechanism, and improving the market credit environment for promoting investment in EPC projects are provided.

This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things computing. Considering the characteristics of IoT data processing, similar to mainstream high performance computing, we use a GPU cluster to achieve better IoT services. Firstly, we present an energy consumption calculation method (ECCM) based on WSN. Then, using the CUDA Programming model, we propose a Two-level Parallel Optimization Model (TLPOM) which exploits reasonable resource planning and common compiler optimization techniques to obtain the best blocks and threads configuration considering the resource constraints of each node. The key to this part is dynamic coupling Thread-Level Parallelism (TLP) and Instruction-Level Parallelism (ILP) to improve the performance of the algorithms without additional energy consumption. Finally, combining the ECCM and the TLPOM, we use the Reliable GPU Cluster Architecture (RGCA) to obtain a high-reliability computing system considering the nodes’ diversity, algorithm characteristics, etc. The results show that the performance of the algorithms significantly increased by 34.1%, 33.96% and 24.07% for Fermi, Kepler and Maxwell on average with TLPOM and the RGCA ensures that our IoT computing system provides low-cost and high-reliability services.

The advancement in science and technology has led to luffa sponge (LS) being widely used as a natural material in industrial application as its polyporous structure and light texture. In order to enhance the utility of LS fibers as the reinforcement of lightweight composite materials, this study investigate its water absorption, mechanical properties, anatomical characteristic and thermal performance. Hence, moisture regain, tensile properties of LS fiber bundles were measured in accordance with standards and the structural characteristics were investigated via microscopic observation. Scanning electron microscopy (SEM) was used to observe the surface morphology and fracture surface of fiber bundles. Test results shows that the special structure where the phloem tissues degenerate to cavities had a significant influence on the mechanical properties of LS fiber bundles. Additionally, the transverse sectional area occupied by fibers in a fiber bundle (SF), wall thickness and ratio of wall to lumen of fiber cell, and crystallinity of cellulose had an impact on the mechanical properties of LS fiber bundles. Furthermore, the fiber bundles density of LS varies range of 385.46-468.70 kg/m³, much less than that of jute (1360.40 kg/m³) and Arenga engleri (950.20 kg/m³) while LS fiber bundles has superior specific modulus.

The oscillating heat pipe (OHP) is a new member in the family of heat pipes, and it has great potential applications in energy conservation. However, the fluid flow and heat transfer in the OHP as well as the fundamental effects of inner diameter on them have not been fully understood, which are essential to the design and optimization of the OHP in real applications. Therefore, by combining the high-speed visualization method and infrared thermal imaging technique, the fluid flow and thermal performance in the OHPs with inner diameters of 1, 2 and 3 mm are presented and analyzed. The results indicate that three fluid flow motions, including small oscillation, bulk oscillation and circulation, coexist or, respectively, exist alone with the increasing heating load under different inner diameters, with three flow patterns occurring in the OHPs, viz. bubbly flow, slug flow and annular flow. These fluid flow motions are closely correlated with the heat and mass transfer performance in the OHPs, which can be reflected by the characteristics of infrared thermal images of condensers. The decrease in the inner diameter increases the frictional flow resistance and capillary instability while restricting the nucleate boiling in OHPs, which leads to a smaller proportion of bubbly flow, a larger proportion of short slug flow, a poorer thermal performance, and easier dry-out of working fluid. In addition, when compared with the 2 mm OHP, the increasing role of gravity induces the thermosyphon effect and weakens the 'bubble pumping' action, which results in a little smaller and bigger thermal resistances of 3 mm OHP under small and bulk oscillation of working fluid, respectively.

This paper formulates the performance evaluation of cloud services as a multicriteria group decision making problem, and presents a fuzzy multicriteria group decision making method for evaluating the performance of cloud services. Interval-valued intuitionistic fuzzy numbers are used to model the inherent subjectiveness and imprecision of the performance evaluation process. An effective algorithm is developed based on the technique for order preference by similarity to ideal solution method and the Choquet integral operator for adequately solving the performance evaluation problem. An example is presented to demonstrate the applicability of the proposed fuzzy multicriteria group decision making method for solving the multicriteria group decision making problem in real world situations.

Prestressed concrete sleepers (or railroad ties) are principally designed in order to carry wheel loads from the rails to the ground of railway tracks. Their design takes into account static and dynamic loading conditions. In spite of the most common use of the prestressed concrete crossties in railway tracks, there have always been many demands from rail engineers to improve serviceability and functionality of concrete crossties. For example, signaling, fiber optic, equipment cables are often damaged either by ballast corners or by tamping machine. There has been a need to re-design concrete crosstie to cater cables internally so that they would not experience detrimental or harsh environments. Also, many concrete crossties need a retrofit for automatic train control device and similar signaling equipment. In contrast, the effects of holes and web openings on structural capacity of concrete crossties have not been thoroughly investigated. This paper accordingly highlights the effect of holes and web openings on the toughness and ductility of concrete crossties. The outcome of this research enables better decision making process for retrofiting prestressed concrete crossties with holes and web opening in practice.

Low Power Wide Area Networks (LPWAN) enable a growing number of Internet-of-Things (IoT) applications with large geographical coverage, low bit-rate, and long lifetime requirements. LoRa (Long Range) is a well-known LPWAN technology that uses a proprietary Chirp Spread Spectrum (CSS) physical layer, while the upper layers are defined by an open standard - LoRaWAN. In this paper, we propose a simple yet effective method to improve the Quality-of-Service (QoS) of LoRa networks by fine-tuning specific radio parameters. Through a Mixed Integer Linear Programming (MILP) problem formulation, we find optimal settings for the Spreading Factor (SF) and Carrier Frequency (CF) radio parameters, considering the network traffic specifications as a whole, to improve the Data Extraction Rate (DER) and to reduce the packet collision rate and the energy consumption in LoRa networks. The effectiveness of the optimization procedure is demonstrated by simulations, using LoRaSim for different network scales. In relation to the traditional LoRa radio parameter assignment policies, our solution leads to an average increase of 6% in DER, and a number of collisions 13 times smaller. In comparison to networks with dynamic radio parameter assignment policies, there is an increase of 5%, 2.8%, and 2% of DER, and a number of collisions 11, 7.8 and 2.5 times smaller than equal-distribution, Tiurlikova's (SoTa), and random distribution, respectively. Regarding the network energy consumption metric, the proposed optimization obtained an average consumption similar to Tiurlikova's, and 2.8 times lower than the equal-distribution and random dynamic allocation policies. Furthermore, we approach the practical aspects of how to implement and integrate the optimization mechanism proposed in LoRa, guaranteeing backward compatibility with the standard protocol.

Event detection provides a crucial foundation for intelligent text analysis and supports numerous downstream applications. However, existing detection models often fail to meet the high accuracy requirements and typically require a human–machine collaborative detection mode involving “machine detection followed by manual audit and correction.” Analysis reveals that the recall rate of machine detection is a major factor limiting the efficiency of human–machine collaboration. To address this at its root and ensure high recall, an event trigger recommendation task is introduced, and a span-based recommendation model for Chinese, SpETR (Span-based Event Trigger Recommender), is developed. This model integrates confidence information from both trigger identification and event classification stages to recommend candidate triggers and their event types for each event. To enhance recall, a semantic boundary smoothing method is proposed, which assigns soft labels to spans around gold triggers based on semantic completeness and part-of-speech, combined with a modified focal loss function to make the model predictions smoother. Experiments on DuEE and a self-built dataset show that SpETR is most effective when the number of recommendations is set to 3, achieving recall rates of 97.76% and 98.70%, respectively, comprising improvements of 4.30% and 5.22% over the optimal baseline models. In terms of human–machine collaborative detection, SpETR saved 30.6% and 25.8% of time compared to traditional detection models on two datasets, and the average F1 score of the annotation results was also improved by 5.35% and 3.48%, respectively.

The electric vehicle market is constantly evolving, with research and development efforts to improve motor technologies and address current challenges to meet the growing demand for sustainable transportation solutions well underway. Electric vehicles are crucial to the global initiative to reduce carbon emissions. The core component of an electric vehicle is its motor drive technology, which has seen significant advancements and diversification in recent years. Although alternating-current motors, particularly induction and synchronous motors, are widely used for their efficiency and low maintenance, direct-current motors provide high torque and cost-effectiveness advantages. This study examines various electric motor technologies used in electric vehicles and compares them using several parameters such as reliability, cost, and efficiency. This study presents a multi-criteria comparison of the various electric motors used in the electric traction system to provide a picture that enables selecting the appropriate electrical motor for the intended application. Although the permanent magnet synchronous motor appears to be the popular choice among electric car makers, the proposed comparative study demonstrates that the induction motor matches the essential requirements of electric vehicles.

When solar energy is converted into electricity by photovoltaic modules, only 20% of the incident solar radiation is converted into electricity and the remaining 80% is converted into heat, increasing the temperature of the photovoltaic solar cells. The increase in PV module temperature has a negative impact on open-circuit voltage. This leads to a reduction in electrical efficiency and degradation of the photovoltaic modules. In order to maintain their operating temperature under standard test conditions, it is important to remove the excess heat from the photovoltaic solar cells by cooling. After cooling, the temperature of the PV modules decreases and the electrical efficiency is improved. In this article, air cooling techniques for photovoltaic modules are examined. The disadvantages and prospects of the different approaches to these air-cooling techniques are presented. Understanding the different cooling techniques is important for improving the electricity production of photovoltaic modules and for popularising this technology.

Post-exercise recovery is fundamental to optimizing athletic performance, focusing on muscle repair, glycogen replenishment, rehydration, and reducing exercise-induced inflammation. This review examines the evolving landscape of recovery nutrition, highlighting the transition from conventional supplements—such as protein, carbohydrates, creatine, and branched-chain amino acids (BCAAs)—to functional foods rich in bioactive compounds. Emerging evidence supports the efficacy of functional foods like tart cherry juice, turmeric, and omega-3 fatty acids in mitigating oxidative stress and inflammation, thus accelerating recovery. Additionally, probiotics and prebiotic-rich foods are gaining recognition for enhancing gut health, promoting nutrient absorption, and strengthening immune function, which are crucial in recovery processes. The concept of personalized nutrition, guided by genetic and metabolic profiling, is explored as a promising approach to tailor recovery strategies to individual physiological needs. Continued research into the long-term effects of supplements, the role of functional foods, and nutrient interactions is essential for developing more comprehensive and individualized recovery protocols. Integrating functional foods with personalized nutrition offers a holistic strategy to enhance recovery, optimize performance, and promote long-term health in athletes.

In this investigation, four distinct by-products of natural materials were used to compose a mix for rammed earth construction. The mix of these materials, which have various granulometry, affords many potential combinations, making the analysis of different combinations highly complex. The Taguchi method, a statistical approach renowned for significantly reducing the number of ex-periments in complex systems, was employed to address this challenge. Each of the four ma-terials was assessed across four different levels, with moisture content also factored in as a pa-rameter within the statistical analysis. Two separate studies were conducted to obtain two optimal com-binations of the materials to enhance the dry density and the Unconfined Compressive Strength (UCS). Taguchi method demonstrated its efficacy in predicting the optimal combination of mix-tures for enhancing both objective parameters. A natural by-product mix demonstrated its po-tential for use as a building material. The enhancement of the dry density due to a modification of the mix’s Particle Size Distribution (PSD) did not produce a direct improvement in the mix UCS. The factor to be prioritized should be the mechanical strength, rather than the dry density of the sample.